This document presents a method for human identification using gait recognition. It extracts statistical gait features from Speeded-Up Robust Features (SURF) descriptors applied to binary, roughness, and gray-scale images of a person's gait cycle. Specifically, it calculates 12 statistical features including mean, root mean square, skewness, and kurtosis from the SURF descriptors of the three image types. A support vector machine classifier is used to evaluate the discriminatory ability of the extracted statistical gait features for human identification. The method is tested on the CASIA-B gait dataset and aims to improve recognition accuracy under variations in clothing, carrying conditions, and viewing angles.
Gait is the style of walking or limb movement of a
person. Gait recognition is a biometric technology that is based
on behavioral features of human. It finds applications in different
areas such as banks, military, airports, and many other areas for
threat detection and security purposes. Biometric gait recognition
is a popular area of research as it is an unobtrusive process to
recognize a person. In the current paper we review several
approaches of gait recognition, discuss their advantages and
disadvantages and then show directions for future research.
BIOMETRIC AUTHORIZATION SYSTEM USING GAIT BIOMETRYIJCSEA Journal
ย
ABSTRACT
Human gait, which is a new biometric aimed to recognize individuals by the way they walk have come to play an increasingly important role in visual surveillance applications. In this paper a novel hybrid holistic approach is proposed to show how behavioural walking characteristics can be used to recognize unauthorized and suspicious persons when they enter a surveillance area. Initially background is modelled from the input video captured from cameras deployed for security and the foreground moving object in the individual frames are segmented using the background subtraction algorithm. Then gait representing spatial, temporal and wavelet components are extracted and fused for training and testing multi class support vector machine models (SVM). The proposed system is evaluated using side view videos of NLPR database. The experimental results demonstrate that the proposed system achieves a pleasing recognition rate and also the results indicate that the classification ability of SVM with Radial Basis Function (RBF) is better than with other kernel functions.
This document presents a human identification system using gait biometrics. The system first detects moving subjects in video sequences and extracts silhouettes using background subtraction. It then uses Speeded Up Robust Features (SURF) to detect keypoints and extract descriptors, which are used to calculate gait features like joint angles and velocities. These gait features are classified using Meta-sample based Sparse Representation Classification (MSRC) which achieves an overall classification rate of 94.6782% on a self-collected dataset.
This document summarizes research on human motion tracking techniques using skeleton models. It discusses how model-based approaches use a predefined human skeleton model to represent joints and segments. Video-based approaches can infer physical attributes and daily actions without sensors. The document reviews several papers on reconstructing 3D human pose from video, using reduced joint sets and shape models to filter noise and track landmarks, and developing multi-view pose tracking using generative sampling and physical constraints. It also discusses challenges like high degrees of freedom and self-occlusion, and the need for efficient algorithms to enable real-time 3D full-body motion tracking from multiple cameras.
This document proposes using gait as a biometric for human identification. It discusses extracting image features from a person's silhouette and gait cycle, including the width of their outer contour and their entire binary silhouette. Two approaches are explored: the indirect approach transforms these high-dimensional image features into lower dimensions before using an HMM for representation, while the direct approach uses the features directly with an HMM. The document outlines issues with existing identification systems and argues that gait recognition could provide a more unique, reliable means of identification than alternatives like signatures or facial recognition.
Principal component analysis for human gait recognition systemjournalBEEI
ย
This paper represents a method for Human Recognition system using Principal Component Analysis. Human Gait recognition works on the gait of walking subjects to identify people without them knowing or without their permission. The initial step in this kind of system is to generate silhouette frames of walking human. A number of features couldb be exytacted from these frames such as centriod ratio, heifht, width and orientation. The Principal Component Analysis (PCA) is used for the extracted features to condense the information and produces the main components that can represent the gait sequences for each waiking human. In the testing phase, the generated gait sequences are recognized by using a minimum distance classifier based on eluclidean distance matched with the one that already exist in the database used to identify walking subject
Human gait recognition using preprocessing and classification techniques IJECEIAES
ย
Biometric recognition systems have been attracted numerous researchers since they attempt to overcome the problems and factors weakening these systems including problems of obtaining images indeed not appearing the resolution or the object completely. In this work, the object movement reliance was considered to distinguish the human through his/her gait. Some losing features probably weaken the systemโs capability in recognizing the people, hence, we propose using all data recorded by the Kinect sensor with no employing the feature extraction methods based on the literature. In these studies, coordinates of 20 points are recorded for each person in various genders and ages, walking with various directions and speeds, creating 8404 constraints. Moreover, pre-processing methods are utilized to measure its influences on the system efficiency through testing on six types of classifiers. Within the proposed approach, a noteworthy recognition rate was obtained reaching 91% without examining the descriptors.
Gait is the style of walking or limb movement of a
person. Gait recognition is a biometric technology that is based
on behavioral features of human. It finds applications in different
areas such as banks, military, airports, and many other areas for
threat detection and security purposes. Biometric gait recognition
is a popular area of research as it is an unobtrusive process to
recognize a person. In the current paper we review several
approaches of gait recognition, discuss their advantages and
disadvantages and then show directions for future research.
BIOMETRIC AUTHORIZATION SYSTEM USING GAIT BIOMETRYIJCSEA Journal
ย
ABSTRACT
Human gait, which is a new biometric aimed to recognize individuals by the way they walk have come to play an increasingly important role in visual surveillance applications. In this paper a novel hybrid holistic approach is proposed to show how behavioural walking characteristics can be used to recognize unauthorized and suspicious persons when they enter a surveillance area. Initially background is modelled from the input video captured from cameras deployed for security and the foreground moving object in the individual frames are segmented using the background subtraction algorithm. Then gait representing spatial, temporal and wavelet components are extracted and fused for training and testing multi class support vector machine models (SVM). The proposed system is evaluated using side view videos of NLPR database. The experimental results demonstrate that the proposed system achieves a pleasing recognition rate and also the results indicate that the classification ability of SVM with Radial Basis Function (RBF) is better than with other kernel functions.
This document presents a human identification system using gait biometrics. The system first detects moving subjects in video sequences and extracts silhouettes using background subtraction. It then uses Speeded Up Robust Features (SURF) to detect keypoints and extract descriptors, which are used to calculate gait features like joint angles and velocities. These gait features are classified using Meta-sample based Sparse Representation Classification (MSRC) which achieves an overall classification rate of 94.6782% on a self-collected dataset.
This document summarizes research on human motion tracking techniques using skeleton models. It discusses how model-based approaches use a predefined human skeleton model to represent joints and segments. Video-based approaches can infer physical attributes and daily actions without sensors. The document reviews several papers on reconstructing 3D human pose from video, using reduced joint sets and shape models to filter noise and track landmarks, and developing multi-view pose tracking using generative sampling and physical constraints. It also discusses challenges like high degrees of freedom and self-occlusion, and the need for efficient algorithms to enable real-time 3D full-body motion tracking from multiple cameras.
This document proposes using gait as a biometric for human identification. It discusses extracting image features from a person's silhouette and gait cycle, including the width of their outer contour and their entire binary silhouette. Two approaches are explored: the indirect approach transforms these high-dimensional image features into lower dimensions before using an HMM for representation, while the direct approach uses the features directly with an HMM. The document outlines issues with existing identification systems and argues that gait recognition could provide a more unique, reliable means of identification than alternatives like signatures or facial recognition.
Principal component analysis for human gait recognition systemjournalBEEI
ย
This paper represents a method for Human Recognition system using Principal Component Analysis. Human Gait recognition works on the gait of walking subjects to identify people without them knowing or without their permission. The initial step in this kind of system is to generate silhouette frames of walking human. A number of features couldb be exytacted from these frames such as centriod ratio, heifht, width and orientation. The Principal Component Analysis (PCA) is used for the extracted features to condense the information and produces the main components that can represent the gait sequences for each waiking human. In the testing phase, the generated gait sequences are recognized by using a minimum distance classifier based on eluclidean distance matched with the one that already exist in the database used to identify walking subject
Human gait recognition using preprocessing and classification techniques IJECEIAES
ย
Biometric recognition systems have been attracted numerous researchers since they attempt to overcome the problems and factors weakening these systems including problems of obtaining images indeed not appearing the resolution or the object completely. In this work, the object movement reliance was considered to distinguish the human through his/her gait. Some losing features probably weaken the systemโs capability in recognizing the people, hence, we propose using all data recorded by the Kinect sensor with no employing the feature extraction methods based on the literature. In these studies, coordinates of 20 points are recorded for each person in various genders and ages, walking with various directions and speeds, creating 8404 constraints. Moreover, pre-processing methods are utilized to measure its influences on the system efficiency through testing on six types of classifiers. Within the proposed approach, a noteworthy recognition rate was obtained reaching 91% without examining the descriptors.
This document provides a literature review of different control mechanisms that have been used for autonomous wheelchairs. It discusses control mechanisms based on image analysis using head gestures and eye tracking, bio-potential signals like EMG and EOG, motion signals using head and hand gestures, and voice signals. For each method, some examples of systems developed are described along with the algorithms and techniques used. The review covers issues with different approaches and highlights some algorithms that have shown high accuracy like Adaboost for face detection and TICA/MRP for identity authentication.
Osteoarthritis (OA) is the most common form of arthritis seen in aged or older populations. It is caused
because of a degeneration of articular cartilage, which functions as shock absorption cushion in knee joint. OA
also leads sliding of bones together, cause swelling, pain, eventually and loss of motion. Nowadays, magnetic
resonance imaging (MRI) technique is widely used in the progression of osteoarthritis diagnosis due to the ability
to display the contrast between bone and cartilage. Usually, analysis of MRI image is done manually by a
physician which is very unpredictable, subjective and time consuming. Hence, there is need to develop automated
system to reduce the processing time. In this paper, a new automatic knee OA detection system based on feature
extraction and artificial neural network is developed. The different features viz GLCM texture, statistical, shape
etc. is extracted by using different image processing algorithms. This detection system consists of 4 stages, which
are pre-processing with ROI cropping, segmentation, feature extraction, and classification by neural network. This
technique results 98.5% of classification accuracy at training stage and 92% at testing stage.
Keywords โ Artificial Neural Network (ANN), Gray Level Co-occurrence Matrix (GLCM),Knee
Joint, Magnetic Resonance Imaging (MRI), Osteoarthritis(OA).
This document describes a human-tracking robot that uses ultra-wideband (UWB) technology. It proposes using a modified hyperbolic positioning algorithm and virtual spring model to detect, locate, and track a target person in real-time. The robot is equipped with UWB anchors and ultrasound sensors, and an embedded control board processes sensor data to drive motors for following movements. An advantage of the UWB method over computer vision is robustness to varying lighting conditions outdoors. Experimental results demonstrate the tracking performance of the robot.
An Automated Pelvic Bone Geometrical Feature Measurement Utilities on Ct Scan...IOSR Journals
ย
This document discusses an automated system for measuring geometric features of the pelvic bone from CT scan images. The system uses patch statistical shape models and a multilevel measurement utility to determine pelvic orientation based on image calibration. It aims to help orthopedic surgeons locate damage areas and landmarks more accurately, especially for obese patients where manual palpation is difficult. The system involves experts to analyze statistical values generated from the measurements to inform treatment decisions.
IRJET- Behavior Analysis from Videos using Motion based Feature ExtractionIRJET Journal
ย
This document proposes a technique for analyzing human behavior in videos using motion-based feature extraction. It discusses how previous approaches have used spatial and temporal features to detect abnormal behaviors. The proposed approach extracts motion features from videos to represent each video with a single feature vector, rather than extracting features from each individual frame. This reduces the feature space and unnecessary information. The technique involves preprocessing videos into frames, extracting motion features, using KNN classification on the features to classify behaviors as normal or abnormal, and evaluating the method's performance on various metrics like accuracy, recall, and precision. Testing on fight and riot datasets showed the motion-based approach achieved higher accuracy, recall, precision and F-measure than a non-motion based approach.
Human Segmentation Using Haar-ClassifierIJERA Editor
ย
Segmentation is an important process in many aspects of multimedia applications. Fast and perfect segmentation of moving objects in video sequences is a basic task in many computer visions and video investigation applications. Particularly Human detection is an active research area in computer vision applications. Segmentation is very useful for tracking and recognition the object in a moving clip. The motion segmentation problem is studied and reviewed the most important techniques. We illustrate some common methods for segmenting the moving objects including background subtraction, temporal segmentation and edge detection. Contour and threshold are common methods for segmenting the objects in moving clip. These methods are widely exploited for moving object segmentation in many video surveillance applications, such as traffic monitoring, human motion capture. In this paper, Haar Classifier is used to detect humans in a moving video clip some features like face detection, eye detection, full body, upper body and lower body detection.
Knee Joint Articular Cartilage Segmentation using Radial Search Method, Visua...CSCJournals
ย
Knee is a complex and highly stressed joint of the human body. Articular Cartilage is a smooth hyaline spongy material between the tibia and femur bones of knee joint. Cartilage morphology change is an important biomarker for the progression of osteoarthritis (OA). Magnetic Resonance Imaging (MRI) is the modality widely used to image the knee joint because of its hazard free and soft tissue contrast. Cartilage thickness measurement and visualization is useful for early detection and progression of the disease in case of OA affected patients. In the present work, knee joint MR images of normal and OA affected are processed for segmentation and visualization of cartilage using semiautomatic method. The radial search method is used with minor modifications in search area to reduce computation time. Cartilage thickness and volume is measured in lateral, medial and patellar regions of femur. The overall accuracy of measurements is determined by comparing the measurements with another semiautomatic method based on edge detection and interpolation. It is observed a good correlation between quantification of cartilage in two methods. The method takes less time for segmentation because of reduced manual steps. The reduced cartilage thickness and volume is observed in OA affected knee of different level of progression.
This document discusses a novel approach for person re-identification using unsupervised feature learning. First, patch matching is used to handle misalignment from viewpoint and pose changes between camera views. Second, human attributes are learned in an unsupervised manner to extract discriminative and repeatable features. These attributes include small but distinctive objects like backpacks or folders. Incorporating attribute information improves matching accuracy. The proposed approach learns features without requiring labeled training data, making it more adaptable to new camera settings.
Feedback method based on image processing for detecting human body via flying...ijaia
ย
Image-processing is one the challenging issue in robotic as well as electrical engineering research
contexts. This study proposes a system for extract and tracking objects by a quadcopterโs flying robot and
how to extract the human body. It is observed in image taken from real-time camera that is embedded
bottom of the quadcopter, there is a variance in human behaviour being tracked or recorded such as
position and, size, of the human. In the regard, the paper tries to investigate an image-processing method
for tracking humansโ body, concurrently. For this process, an extraction method, which defines features to
distinguish a human body, is proposed. The proposed method creates a virtual shape of bodies for
recognizing the body of humans, also, generate an extractor according to its edge information. This method
shows better performance in term of precision as well as speed experimentally
IMAGINARY ANATOMY LINE MEASUREMENTS ON THE THORAXAM Publications
ย
An imaginary line measurement of the thorax is important for clinical need. There are several imaginary anatomical lines on the thorax that can be measured directly using a tape meter, such as: midclavicular line, midaxilla line, chest width, chest circumference, distance of incisura jugularis sterni to the processusxiphoideus, intermidclavicular line, the upper thoracic dome and the lower thoracic dome. The objective of this article is to provide information on the average anatomical imaginary line value on the thoracic of the adult male. The data was then used for manufacturing of a thoracic anatomical phantom. Some marks of imaginary lines formed by clavicula, costae, and sternum were used as a reference in measurement. The anatomical imaginary line measurements were performed using a tape meter directly on 10 adult male samples, and carried out based on Chest X ray image of the same samples on a Computer Radiography (CR) workstation computer. Both measurements were then analyzed; ultrasonography examination was used to get soft tissue thickness for correction. Average values for midclavicular line variable of measurement using a tape measure was (29.10 ยฑ 1.80) cm and the average value for the midclavicular line variable of measurement using Chest X ray on a CR workstation computer was (21.24 ยฑ 0.73) cm. The average values for the variables intermidclavicular line measurement using a tape measure was (19.60 ยฑ 0.69) cm and the average value for the variable intermidclavicular line of measurement using Chest X ray on a CR workstation computer was (16.53 ยฑ 1.19) cm.
This document presents a human identification system using gait recognition. The system first detects moving subjects in video sequences and extracts silhouettes using background subtraction. It then calculates motion parameters like joint angles and gait velocity from the silhouettes using Speeded Up Robust Features (SURF) descriptors. These motion parameters are classified using a Meta-sample based sparse representation method, achieving an overall classification rate of 94.6782% on a test dataset. The system provides view-invariant human identification through gait analysis.
A Parametric Approach to Gait Signature Extraction for Human Motion Identific...CSCJournals
ย
The extraction and analysis of human gait characteristics using image sequences are currently an intense area of research. Identifying individuals using biometric methods has recently gained growing interest from computer vision researchers for security purposes at places like airport, banks etc. Gait recognition aims essentially to address this problem by identifying people at a distance based on the way they walk i.e., by tracking a number of feature points or gait signatures. We describe a new model-based feature extraction analysis is presented using Hough transform technique that helps to read the essential parameters used to generate gait signatures that automatically extracts and describes human gait for recognition. In the preprocessing steps, the picture frames taken from video sequences are given as input to Canny edge detection algorithm which helps to detect edges of the image by extracting foreground from background also it reduces the noise using Gaussian filter. The output from edge detection is given as input to the Hough transform. Using the Hough transform image, a clear line based model is designed to extract gait signatures. A major difficulty of the existing gait signature extraction methods are the good tracking the requisite feature points. In the proposed work, we have used five parameters to successfully extract the gait signatures. It is observed that when the camera is placed at 90 and 270 degrees, all the parameters used in the proposed work are clearly visible. The efficiency of the model is tested on a variety of body position and stride parameters recovered in different viewing conditions on a database consisting of 20 subjects walking at both an angled and frontal-parallel view with respect to the camera, both indoors and outdoors and find the method to be highly successful. The test results show good clarity rates, with a high level of confidence and it is suggested that the algorithm reported here could form the basis of a robust system for monitoring of gait.
Using skeleton model to recognize human gait genderIAESIJAI
ย
Biometrics became fairly important to help people identifications persons by their individualities or features. In this paper, gait recognition has been based on a skeleton model as an important indicator in prevalent activities. Using the reliable dataset for the Chinese Academy of Sciences (CASIA) of silhouettes class C database. Each video has been discredited to 75 frames for each (20 persons (10 males and 10 females)) as (1.0), the result will be 1,500 frames. After Pre-processing the images, many features are extracted from human silhouette images. For gender classification, the human walking skeleton used in this study. The model proposed is based on morphological processes on the silhouette images. The common angle has been computed for the two legs. Later, principal components analysis (PCA) was applied to reduce data using feature selection technology to get the most useful information in gait analysis. Applying two classifiers artificial neural network (ANN) and Gaussian Bayes to distinguish male or female for each classifier. The experimental results for the suggested method provided significant accomplishing about (95.5%), and accuracy of (75%). Gender classification using ANN is more efficient from the Gaussian Bayes technique by (20%), where ANN technique has given a superior performance in recognition.
Robust Human Tracking Method Based on Apperance and Geometrical Features in N...csandit
ย
This paper proposes a robust tracking method which concatenates appearance and geometrical
features to re-identify human in non-overlapping views. A uniformly-partitioning method is
proposed to extract local HSV(Hue, Saturation, Value) color features in upper and lower
portion of clothing. Then adaptive principal view selecting algorithm is presented to locate
principal view which contains maximum appearance feature dimensions captured from different
visual angles. For each appearance feature dimension in principal view, all its inner frames get
involved in training a support vector machine (SVM). In matching process, human candidate
filtering is first operated with an integrated geometrical feature which connects height estimate
with gait feature. The appearance features of the remaining human candidates are later tested
by SVMs to determine the objectโs existence in new cameras. Experimental results show the
feasibility and effectiveness of this proposal and demonstrate the real-time in appearance
feature extraction and robustness to illumination and visual angle change.
ROBUST HUMAN TRACKING METHOD BASED ON APPEARANCE AND GEOMETRICAL FEATURES IN ...cscpconf
ย
This paper proposes a robust tracking method which concatenates appearance and geometrical
features to re-identify human in non-overlapping views. A uniformly-partitioning method is
proposed to extract local HSV(Hue, Saturation, Value) color features in upper and lower
portion of clothing. Then adaptive principal view selecting algorithm is presented to locate
principal view which contains maximum appearance feature dimensions captured from different
visual angles. For each appearance feature dimension in principal view, all its inner frames get
involved in training a support vector machine (SVM). In matching process, human candidate
filtering is first operated with an integrated geometrical feature which connects height estimate
with gait feature. The appearance features of the remaining human candidates are later tested
by SVMs to determine the objectโs existence in new cameras. Experimental results show the
feasibility and effectiveness of this proposal and demonstrate the real-time in appearance
feature extraction and robustness to illumination and visual angle change.
This document presents a method for classifying gender from human gait using silhouette images. The silhouette is divided into two regions, and features like moments and ellipse parameters are extracted from each region. These features are used to form a feature vector for each frame. Mean and standard deviation features are then calculated across frames. Different classifiers like K-Nearest Neighbor and Support Vector Machine are tested on the CASIA gait dataset, with SVM found to perform better, achieving a 93.33% recognition rate using linear kernels.
To identify the person using gait knn based approacheSAT Journals
ย
Abstract In human identification, the process of identifying the person by their gait is an emerging research trend in the field of visual surveillance. Gait is a new biometrics, has been recently used to recognize a person via style of his walking. While person walking variation becomes take place in different parts of body. On the basis of these variations, proposed method is evaluated on CASIA gait database by using K-nearest Neighbor classifier. Experimental results demonstrate that the proposed method has an encouraging recognition performance also the results indicate that the classification ability of KNN with correlation measure perform better than with other type of distance measure functions. Keywords: Gait biometrics, KNN, visual surveillance, CASIA, silhouette.
Symbolic representation and recognition of gait an approach based on lbp of ...sipij
ย
Gait is one of the biometric techniques used to identify an individual from a distance by his/her walking
style. Gait can be recognized by studying the static and dynamic part variations of individual body contour
during walk. In this paper, an interval value based representation and recognition of gait using local
binary pattern (LBP) of split gait energy images is proposed. The gait energy image (GEI) of a subject is
split into four equal regions. LBP technique is applied to each region to extract features and the extracted
features are well organized. The proposed representation technique is capable of capturing variations in
gait due to change in cloth, carrying a bag and different instances of normal walking conditions more
effectively. Experiments are conducted on the standard and considerably large database (CASIA database
B) and newly created University of Mysore (UOM) gait dataset to study the efficacy of the proposed gait
recognition system. The proposed system being robust to handle variations has shown significant
improvement in recognition rate.
Accurate metaheuristic deep convolutional structure for a robust human gait r...IJECEIAES
ย
Gait recognition has become a developing technology in various security, industrial, medical, and military applications. This paper proposed a deep convolutional neural network (CNN) model to authenticate humans via their walking style. The proposed model has been applied to two commonly used standardized datasets, Chinese Academy of Sciences (CASIA) and Osaka University-Institute of Scientific and Industrial Research (OU-ISIR). After the silhouette images have been isolated from the gait image datasets, their features have been extracted using the proposed deep CNN and the traditional ones, including AlexNet, Inception (GoogleNet), VGGNet, ResNet50, and Xception. The best features were selected using genetic, grey wolf optimizer (GWO), particle swarm optimizer (PSO), and chi-square algorithms. Finally, recognize the selected features using the proposed deep neural network (DNN). Several performance evaluation parameters have been estimated to evaluate the modelโs quality, including accuracy, specificity, sensitivity, false negative rate (FNR), and training time. Experiments have demonstrated that the suggested framework with a genetic feature selector outperforms previous selectors and recent research, scoring accuracy values of 99.46% and 99.09% for evaluating the CASIA and
OU-ISIR datasets, respectively, in low time (19 seconds for training).
Health monitoring catalogue based on human activity classification using mac...IJECEIAES
ย
In recent times, fitness trackers and smartphones equipped with different sensors like gyroscopes, accelerometers, global positioning system sensors and programs are used for recognizing human activities. In this paper, the results collected from these devices are used to design a system that can assist an application in monitoring a personโs health. The proposed system takes the raw sensor signals as input, preprocesses it and using machine learning techniques outputs the state of the user with minimum error. The objective of this paper is to compare the performance of different algorithms logistic regression (LR), support vector machine (SVM), k-nearest neighbor (k-NN) and random forest (RF). The algorithms are trained and tested with an original number of features as well as with transformed number of features (using linear discriminant analysis). The data with a smaller number of features is then used to visualize the high dimensional data. In this paper, each data point is mapped in the high dimensional data to two-dimensional data using t-distributed stochastic neighbor embedding technique. Overall, the first high dimensional data is visualized and compared with modelโs performance with different algorithms and different number of coordinates.
The document summarizes a research paper on crowd behavior analysis using a graph theoretic approach. It proposes a model called the Graph theoretic approach based Crowd Behavior Analysis and Classification System (GCBACS). The key points are:
1) GCBACS uses optical flow to track personnel trajectories in video frames and derive streak flow vectors to analyze crowd behavior.
2) It represents each video frame as a graph and analyzes similarities and variances between frames to classify activities as normal or abnormal.
3) Inter-personal activities are considered for analysis, allowing it to work in dense and sparse crowds. If the cumulative variance between frames exceeds a threshold, the activity is classified as abnormal.
Recently, the demand for surveillance system is increasing in real time application to enhance the security system. These surveillance systems are mainly used in crowded places such as shopping malls, sports stadium etc. In order to support enhance the security system, crowd behavior analysis has been proven a significant technique which is used for crowd monitoring, visual surveillance etc. For crowd behavior analysis, motion analysis is a crucial task which can be achieved with the help of trajectories and tracking of objects. Various approaches have been proposed for crowd behavior analysis which has limitation for densely crowded scenarios, a new object entering the scene etc. In this work, we propose a new approach for abnormal crowd behavior detection. Proposed approach is a motion based spatio-temporal feature analysis technique which is capable of obtaining trajectories of each detected object. We also present a technique to carry out the evaluation of individual object and group of objects by considering relational descriptors based on their environmental context. Finally, a classification is carried out for detection of abnormal or normal crowd behavior by following patch based process. In the results, we have reported that proposed model is able to achieve better performance when compared to existing techniques in terms of classification accuracy, true positive rate, and false positive rate.
This document provides a literature review of different control mechanisms that have been used for autonomous wheelchairs. It discusses control mechanisms based on image analysis using head gestures and eye tracking, bio-potential signals like EMG and EOG, motion signals using head and hand gestures, and voice signals. For each method, some examples of systems developed are described along with the algorithms and techniques used. The review covers issues with different approaches and highlights some algorithms that have shown high accuracy like Adaboost for face detection and TICA/MRP for identity authentication.
Osteoarthritis (OA) is the most common form of arthritis seen in aged or older populations. It is caused
because of a degeneration of articular cartilage, which functions as shock absorption cushion in knee joint. OA
also leads sliding of bones together, cause swelling, pain, eventually and loss of motion. Nowadays, magnetic
resonance imaging (MRI) technique is widely used in the progression of osteoarthritis diagnosis due to the ability
to display the contrast between bone and cartilage. Usually, analysis of MRI image is done manually by a
physician which is very unpredictable, subjective and time consuming. Hence, there is need to develop automated
system to reduce the processing time. In this paper, a new automatic knee OA detection system based on feature
extraction and artificial neural network is developed. The different features viz GLCM texture, statistical, shape
etc. is extracted by using different image processing algorithms. This detection system consists of 4 stages, which
are pre-processing with ROI cropping, segmentation, feature extraction, and classification by neural network. This
technique results 98.5% of classification accuracy at training stage and 92% at testing stage.
Keywords โ Artificial Neural Network (ANN), Gray Level Co-occurrence Matrix (GLCM),Knee
Joint, Magnetic Resonance Imaging (MRI), Osteoarthritis(OA).
This document describes a human-tracking robot that uses ultra-wideband (UWB) technology. It proposes using a modified hyperbolic positioning algorithm and virtual spring model to detect, locate, and track a target person in real-time. The robot is equipped with UWB anchors and ultrasound sensors, and an embedded control board processes sensor data to drive motors for following movements. An advantage of the UWB method over computer vision is robustness to varying lighting conditions outdoors. Experimental results demonstrate the tracking performance of the robot.
An Automated Pelvic Bone Geometrical Feature Measurement Utilities on Ct Scan...IOSR Journals
ย
This document discusses an automated system for measuring geometric features of the pelvic bone from CT scan images. The system uses patch statistical shape models and a multilevel measurement utility to determine pelvic orientation based on image calibration. It aims to help orthopedic surgeons locate damage areas and landmarks more accurately, especially for obese patients where manual palpation is difficult. The system involves experts to analyze statistical values generated from the measurements to inform treatment decisions.
IRJET- Behavior Analysis from Videos using Motion based Feature ExtractionIRJET Journal
ย
This document proposes a technique for analyzing human behavior in videos using motion-based feature extraction. It discusses how previous approaches have used spatial and temporal features to detect abnormal behaviors. The proposed approach extracts motion features from videos to represent each video with a single feature vector, rather than extracting features from each individual frame. This reduces the feature space and unnecessary information. The technique involves preprocessing videos into frames, extracting motion features, using KNN classification on the features to classify behaviors as normal or abnormal, and evaluating the method's performance on various metrics like accuracy, recall, and precision. Testing on fight and riot datasets showed the motion-based approach achieved higher accuracy, recall, precision and F-measure than a non-motion based approach.
Human Segmentation Using Haar-ClassifierIJERA Editor
ย
Segmentation is an important process in many aspects of multimedia applications. Fast and perfect segmentation of moving objects in video sequences is a basic task in many computer visions and video investigation applications. Particularly Human detection is an active research area in computer vision applications. Segmentation is very useful for tracking and recognition the object in a moving clip. The motion segmentation problem is studied and reviewed the most important techniques. We illustrate some common methods for segmenting the moving objects including background subtraction, temporal segmentation and edge detection. Contour and threshold are common methods for segmenting the objects in moving clip. These methods are widely exploited for moving object segmentation in many video surveillance applications, such as traffic monitoring, human motion capture. In this paper, Haar Classifier is used to detect humans in a moving video clip some features like face detection, eye detection, full body, upper body and lower body detection.
Knee Joint Articular Cartilage Segmentation using Radial Search Method, Visua...CSCJournals
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Knee is a complex and highly stressed joint of the human body. Articular Cartilage is a smooth hyaline spongy material between the tibia and femur bones of knee joint. Cartilage morphology change is an important biomarker for the progression of osteoarthritis (OA). Magnetic Resonance Imaging (MRI) is the modality widely used to image the knee joint because of its hazard free and soft tissue contrast. Cartilage thickness measurement and visualization is useful for early detection and progression of the disease in case of OA affected patients. In the present work, knee joint MR images of normal and OA affected are processed for segmentation and visualization of cartilage using semiautomatic method. The radial search method is used with minor modifications in search area to reduce computation time. Cartilage thickness and volume is measured in lateral, medial and patellar regions of femur. The overall accuracy of measurements is determined by comparing the measurements with another semiautomatic method based on edge detection and interpolation. It is observed a good correlation between quantification of cartilage in two methods. The method takes less time for segmentation because of reduced manual steps. The reduced cartilage thickness and volume is observed in OA affected knee of different level of progression.
This document discusses a novel approach for person re-identification using unsupervised feature learning. First, patch matching is used to handle misalignment from viewpoint and pose changes between camera views. Second, human attributes are learned in an unsupervised manner to extract discriminative and repeatable features. These attributes include small but distinctive objects like backpacks or folders. Incorporating attribute information improves matching accuracy. The proposed approach learns features without requiring labeled training data, making it more adaptable to new camera settings.
Feedback method based on image processing for detecting human body via flying...ijaia
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Image-processing is one the challenging issue in robotic as well as electrical engineering research
contexts. This study proposes a system for extract and tracking objects by a quadcopterโs flying robot and
how to extract the human body. It is observed in image taken from real-time camera that is embedded
bottom of the quadcopter, there is a variance in human behaviour being tracked or recorded such as
position and, size, of the human. In the regard, the paper tries to investigate an image-processing method
for tracking humansโ body, concurrently. For this process, an extraction method, which defines features to
distinguish a human body, is proposed. The proposed method creates a virtual shape of bodies for
recognizing the body of humans, also, generate an extractor according to its edge information. This method
shows better performance in term of precision as well as speed experimentally
IMAGINARY ANATOMY LINE MEASUREMENTS ON THE THORAXAM Publications
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An imaginary line measurement of the thorax is important for clinical need. There are several imaginary anatomical lines on the thorax that can be measured directly using a tape meter, such as: midclavicular line, midaxilla line, chest width, chest circumference, distance of incisura jugularis sterni to the processusxiphoideus, intermidclavicular line, the upper thoracic dome and the lower thoracic dome. The objective of this article is to provide information on the average anatomical imaginary line value on the thoracic of the adult male. The data was then used for manufacturing of a thoracic anatomical phantom. Some marks of imaginary lines formed by clavicula, costae, and sternum were used as a reference in measurement. The anatomical imaginary line measurements were performed using a tape meter directly on 10 adult male samples, and carried out based on Chest X ray image of the same samples on a Computer Radiography (CR) workstation computer. Both measurements were then analyzed; ultrasonography examination was used to get soft tissue thickness for correction. Average values for midclavicular line variable of measurement using a tape measure was (29.10 ยฑ 1.80) cm and the average value for the midclavicular line variable of measurement using Chest X ray on a CR workstation computer was (21.24 ยฑ 0.73) cm. The average values for the variables intermidclavicular line measurement using a tape measure was (19.60 ยฑ 0.69) cm and the average value for the variable intermidclavicular line of measurement using Chest X ray on a CR workstation computer was (16.53 ยฑ 1.19) cm.
This document presents a human identification system using gait recognition. The system first detects moving subjects in video sequences and extracts silhouettes using background subtraction. It then calculates motion parameters like joint angles and gait velocity from the silhouettes using Speeded Up Robust Features (SURF) descriptors. These motion parameters are classified using a Meta-sample based sparse representation method, achieving an overall classification rate of 94.6782% on a test dataset. The system provides view-invariant human identification through gait analysis.
A Parametric Approach to Gait Signature Extraction for Human Motion Identific...CSCJournals
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The extraction and analysis of human gait characteristics using image sequences are currently an intense area of research. Identifying individuals using biometric methods has recently gained growing interest from computer vision researchers for security purposes at places like airport, banks etc. Gait recognition aims essentially to address this problem by identifying people at a distance based on the way they walk i.e., by tracking a number of feature points or gait signatures. We describe a new model-based feature extraction analysis is presented using Hough transform technique that helps to read the essential parameters used to generate gait signatures that automatically extracts and describes human gait for recognition. In the preprocessing steps, the picture frames taken from video sequences are given as input to Canny edge detection algorithm which helps to detect edges of the image by extracting foreground from background also it reduces the noise using Gaussian filter. The output from edge detection is given as input to the Hough transform. Using the Hough transform image, a clear line based model is designed to extract gait signatures. A major difficulty of the existing gait signature extraction methods are the good tracking the requisite feature points. In the proposed work, we have used five parameters to successfully extract the gait signatures. It is observed that when the camera is placed at 90 and 270 degrees, all the parameters used in the proposed work are clearly visible. The efficiency of the model is tested on a variety of body position and stride parameters recovered in different viewing conditions on a database consisting of 20 subjects walking at both an angled and frontal-parallel view with respect to the camera, both indoors and outdoors and find the method to be highly successful. The test results show good clarity rates, with a high level of confidence and it is suggested that the algorithm reported here could form the basis of a robust system for monitoring of gait.
Using skeleton model to recognize human gait genderIAESIJAI
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Biometrics became fairly important to help people identifications persons by their individualities or features. In this paper, gait recognition has been based on a skeleton model as an important indicator in prevalent activities. Using the reliable dataset for the Chinese Academy of Sciences (CASIA) of silhouettes class C database. Each video has been discredited to 75 frames for each (20 persons (10 males and 10 females)) as (1.0), the result will be 1,500 frames. After Pre-processing the images, many features are extracted from human silhouette images. For gender classification, the human walking skeleton used in this study. The model proposed is based on morphological processes on the silhouette images. The common angle has been computed for the two legs. Later, principal components analysis (PCA) was applied to reduce data using feature selection technology to get the most useful information in gait analysis. Applying two classifiers artificial neural network (ANN) and Gaussian Bayes to distinguish male or female for each classifier. The experimental results for the suggested method provided significant accomplishing about (95.5%), and accuracy of (75%). Gender classification using ANN is more efficient from the Gaussian Bayes technique by (20%), where ANN technique has given a superior performance in recognition.
Robust Human Tracking Method Based on Apperance and Geometrical Features in N...csandit
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This paper proposes a robust tracking method which concatenates appearance and geometrical
features to re-identify human in non-overlapping views. A uniformly-partitioning method is
proposed to extract local HSV(Hue, Saturation, Value) color features in upper and lower
portion of clothing. Then adaptive principal view selecting algorithm is presented to locate
principal view which contains maximum appearance feature dimensions captured from different
visual angles. For each appearance feature dimension in principal view, all its inner frames get
involved in training a support vector machine (SVM). In matching process, human candidate
filtering is first operated with an integrated geometrical feature which connects height estimate
with gait feature. The appearance features of the remaining human candidates are later tested
by SVMs to determine the objectโs existence in new cameras. Experimental results show the
feasibility and effectiveness of this proposal and demonstrate the real-time in appearance
feature extraction and robustness to illumination and visual angle change.
ROBUST HUMAN TRACKING METHOD BASED ON APPEARANCE AND GEOMETRICAL FEATURES IN ...cscpconf
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This paper proposes a robust tracking method which concatenates appearance and geometrical
features to re-identify human in non-overlapping views. A uniformly-partitioning method is
proposed to extract local HSV(Hue, Saturation, Value) color features in upper and lower
portion of clothing. Then adaptive principal view selecting algorithm is presented to locate
principal view which contains maximum appearance feature dimensions captured from different
visual angles. For each appearance feature dimension in principal view, all its inner frames get
involved in training a support vector machine (SVM). In matching process, human candidate
filtering is first operated with an integrated geometrical feature which connects height estimate
with gait feature. The appearance features of the remaining human candidates are later tested
by SVMs to determine the objectโs existence in new cameras. Experimental results show the
feasibility and effectiveness of this proposal and demonstrate the real-time in appearance
feature extraction and robustness to illumination and visual angle change.
This document presents a method for classifying gender from human gait using silhouette images. The silhouette is divided into two regions, and features like moments and ellipse parameters are extracted from each region. These features are used to form a feature vector for each frame. Mean and standard deviation features are then calculated across frames. Different classifiers like K-Nearest Neighbor and Support Vector Machine are tested on the CASIA gait dataset, with SVM found to perform better, achieving a 93.33% recognition rate using linear kernels.
To identify the person using gait knn based approacheSAT Journals
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Abstract In human identification, the process of identifying the person by their gait is an emerging research trend in the field of visual surveillance. Gait is a new biometrics, has been recently used to recognize a person via style of his walking. While person walking variation becomes take place in different parts of body. On the basis of these variations, proposed method is evaluated on CASIA gait database by using K-nearest Neighbor classifier. Experimental results demonstrate that the proposed method has an encouraging recognition performance also the results indicate that the classification ability of KNN with correlation measure perform better than with other type of distance measure functions. Keywords: Gait biometrics, KNN, visual surveillance, CASIA, silhouette.
Symbolic representation and recognition of gait an approach based on lbp of ...sipij
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Gait is one of the biometric techniques used to identify an individual from a distance by his/her walking
style. Gait can be recognized by studying the static and dynamic part variations of individual body contour
during walk. In this paper, an interval value based representation and recognition of gait using local
binary pattern (LBP) of split gait energy images is proposed. The gait energy image (GEI) of a subject is
split into four equal regions. LBP technique is applied to each region to extract features and the extracted
features are well organized. The proposed representation technique is capable of capturing variations in
gait due to change in cloth, carrying a bag and different instances of normal walking conditions more
effectively. Experiments are conducted on the standard and considerably large database (CASIA database
B) and newly created University of Mysore (UOM) gait dataset to study the efficacy of the proposed gait
recognition system. The proposed system being robust to handle variations has shown significant
improvement in recognition rate.
Accurate metaheuristic deep convolutional structure for a robust human gait r...IJECEIAES
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Gait recognition has become a developing technology in various security, industrial, medical, and military applications. This paper proposed a deep convolutional neural network (CNN) model to authenticate humans via their walking style. The proposed model has been applied to two commonly used standardized datasets, Chinese Academy of Sciences (CASIA) and Osaka University-Institute of Scientific and Industrial Research (OU-ISIR). After the silhouette images have been isolated from the gait image datasets, their features have been extracted using the proposed deep CNN and the traditional ones, including AlexNet, Inception (GoogleNet), VGGNet, ResNet50, and Xception. The best features were selected using genetic, grey wolf optimizer (GWO), particle swarm optimizer (PSO), and chi-square algorithms. Finally, recognize the selected features using the proposed deep neural network (DNN). Several performance evaluation parameters have been estimated to evaluate the modelโs quality, including accuracy, specificity, sensitivity, false negative rate (FNR), and training time. Experiments have demonstrated that the suggested framework with a genetic feature selector outperforms previous selectors and recent research, scoring accuracy values of 99.46% and 99.09% for evaluating the CASIA and
OU-ISIR datasets, respectively, in low time (19 seconds for training).
Health monitoring catalogue based on human activity classification using mac...IJECEIAES
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In recent times, fitness trackers and smartphones equipped with different sensors like gyroscopes, accelerometers, global positioning system sensors and programs are used for recognizing human activities. In this paper, the results collected from these devices are used to design a system that can assist an application in monitoring a personโs health. The proposed system takes the raw sensor signals as input, preprocesses it and using machine learning techniques outputs the state of the user with minimum error. The objective of this paper is to compare the performance of different algorithms logistic regression (LR), support vector machine (SVM), k-nearest neighbor (k-NN) and random forest (RF). The algorithms are trained and tested with an original number of features as well as with transformed number of features (using linear discriminant analysis). The data with a smaller number of features is then used to visualize the high dimensional data. In this paper, each data point is mapped in the high dimensional data to two-dimensional data using t-distributed stochastic neighbor embedding technique. Overall, the first high dimensional data is visualized and compared with modelโs performance with different algorithms and different number of coordinates.
The document summarizes a research paper on crowd behavior analysis using a graph theoretic approach. It proposes a model called the Graph theoretic approach based Crowd Behavior Analysis and Classification System (GCBACS). The key points are:
1) GCBACS uses optical flow to track personnel trajectories in video frames and derive streak flow vectors to analyze crowd behavior.
2) It represents each video frame as a graph and analyzes similarities and variances between frames to classify activities as normal or abnormal.
3) Inter-personal activities are considered for analysis, allowing it to work in dense and sparse crowds. If the cumulative variance between frames exceeds a threshold, the activity is classified as abnormal.
Recently, the demand for surveillance system is increasing in real time application to enhance the security system. These surveillance systems are mainly used in crowded places such as shopping malls, sports stadium etc. In order to support enhance the security system, crowd behavior analysis has been proven a significant technique which is used for crowd monitoring, visual surveillance etc. For crowd behavior analysis, motion analysis is a crucial task which can be achieved with the help of trajectories and tracking of objects. Various approaches have been proposed for crowd behavior analysis which has limitation for densely crowded scenarios, a new object entering the scene etc. In this work, we propose a new approach for abnormal crowd behavior detection. Proposed approach is a motion based spatio-temporal feature analysis technique which is capable of obtaining trajectories of each detected object. We also present a technique to carry out the evaluation of individual object and group of objects by considering relational descriptors based on their environmental context. Finally, a classification is carried out for detection of abnormal or normal crowd behavior by following patch based process. In the results, we have reported that proposed model is able to achieve better performance when compared to existing techniques in terms of classification accuracy, true positive rate, and false positive rate.
In the fields of sports and health sciences, changes in body shape are one of the most important parameters in order to evaluate the effects of physical training or routine workout performed. Until now, these parameters were typically measured under manually skilled techniques in anthropometry. The purposes of present study were to develop 3D anthropometry and to determine feasibility of the measurements such as lengths, circumferences, body surface area BSA and body or segment volumes with comparing to other conventional methods. The colour information was used to detect the position of land mark seals which was pasted on the skin according to the anatomical basis in human anthropometry. Anthropometric data as well as body surface area and body volume measured by using 3D body scanning technologies might be widely prospective for evaluating the differences or changes in body shape in such fields as health and sports sciences. Mrs. M. Priscilla | Deepika. S | Gayathri. G | Rajalakshmi. M "3D Body Scanning for Human Anthropometry" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33327.pdf Paper Url: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/33327/3d-body-scanning-for-human-anthropometry/mrs-m-priscilla
IRJET - Biometric Traits and Applications of FingerprintIRJET Journal
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This document summarizes research on using biometric traits, particularly fingerprints, for gender identification. It first discusses how fingerprints and other biometric traits can be used for identification and verification. It then reviews several research papers on using fingerprints and other traits like gait and facial recognition for gender classification. The document finds that fingerprints provide 86% accurate results for gender identification due to their permanence and uniqueness. It lists the applications of biometrics in various fields like personal, commercial, government, and forensic use. Finally, it concludes that a proposed algorithm combining fingerprint-based techniques achieves an average 86% accuracy for gender determination.
Wearable sensor-based human activity recognition with ensemble learning: a co...IJECEIAES
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The spectacular growth of wearable sensors has provided a key contribution to the field of human activity recognition. Due to its effective and versatile usage and application in various fields such as smart homes and medical areas, human activity recognition has always been an appealing research topic in artificial intelligence. From this perspective, there are a lot of existing works that make use of accelerometer and gyroscope sensor data for recognizing human activities. This paper presents a comparative study of ensemble learning methods for human activity recognition. The methods include random forest, adaptive boosting, gradient boosting, extreme gradient boosting, and light gradient boosting machine (LightGBM). Among the ensemble learning methods in comparison, light gradient boosting machine and random forest demonstrate the best performance. The experimental results revealed that light gradient boosting machine yields the highest accuracy of 94.50% on UCI-HAR dataset and 100% on single accelerometer dataset while random forest records the highest accuracy of 93.41% on motion sense dataset.
IRJET- Pedestrian Walk Exposure System through Multiple ClassifiersIRJET Journal
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This document proposes a system to help physically challenged people safely cross roads using video monitoring and image processing techniques. The system uses a 1.8m wide walking zone and tracks moving objects using segmentation algorithms. Histogram of Gaussian detection and object detection are used to identify pedestrians. Multiple classifiers including HOG and SVM are employed, achieving an accuracy of 98.5% compared to existing methods. The system aims to provide navigational assistance to visually impaired individuals crossing roads.
Gait Recognition using MDA, LDA, BPNN and SVMIJEEE
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Recognition of any individual is a task to identify the human beings. Human identification using Gait is method to identify an individual by the way he walk or manner of moving on foot of humans. Gait recognition is a type of biometric recognition and related to the behavioral characteristics of biometric recognition. Gait offers ability of distance recognition or at low resolution. In this paper it will present the review of gait recognition system where different approaches and classification categories of Gait recognition like model free and model based approach, MDA, BPNN, LDA, and SVM.
Comparison Analysis of Gait Classification for Human Motion Identification Us...IJECEIAES
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In this paper, it will be discussed about comparison between two kinds of classification methods in order to improve security system based of human gait. Gait is one of biometric methods which can be used to identify person. K-Nearest Neighbour has parallelly implemented with Support Vector Machine for classifying human gait in same basic system. Generally, system has been built using Histogram and Principal Component Analysis for gait detection and its feature extraction. Then, the result of the simulation showed that K-Nearest Neighbour is slower in processing and less accurate than Support Vector Machine in gait classification.
An approach for human gait identification based on areaIOSR Journals
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This document presents a new approach for human gait identification based on calculating the area of a triangle formed between three dynamic body parameters: left hand, right foot, and left foot. Video frames of walking subjects are analyzed to extract these three points in each frame. A triangle is formed and its area is calculated using Heron's formula. The mean area value over multiple frames is stored in a database for each subject. When tested on the CASIA gait dataset, the method achieved an average recognition rate of 88% by comparing the mean area values of unknown subjects to those in the database.
A comparison of multiple wavelet algorithms for iris recognition 2IAEME Publication
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The document compares multiple wavelet algorithms for iris recognition, including complex wavelet transform, Gabor wavelets, and discrete wavelet transform. It first provides background on iris recognition and wavelets. It then describes typical iris recognition systems which involve image acquisition, segmentation, normalization, feature extraction, and matching. Next, it discusses complex wavelets, Gabor wavelets, and discrete wavelet transform for feature extraction in iris recognition. Complex wavelets extract phase and amplitude information to accurately describe oscillating functions. Gabor filters model human visual processing and generate phase-coded bit strings for matching. Discrete wavelet transform uses dyadic wavelet scales and positions for efficient analysis. The paper compares these wavelet algorithms for iris image enhancement,
Similar to Gait Recognition for Person Identification using Statistics of SURF (20)
โSix Sigma Techniqueโ A Journey Through its Implementationijtsrd
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The manufacturing industries all over the world are facing tough challenges for growth, development and sustainability in todayโs competitive environment. They have to achieve apex position by adapting with the global competitive environment by delivering goods and services at low cost, prime quality and better price to increase wealth and consumer satisfaction. Cost Management ensures profit, growth and sustainability of the business with implementation of Continuous Improvement Technique like Six Sigma. This leads to optimize Business performance. The method drives for customer satisfaction, low variation, reduction in waste and cycle time resulting into a competitive advantage over other industries which did not implement it. The main objective of this paper โSix Sigma Technique A Journey Through Its Implementationโ is to conceptualize the effectiveness of Six Sigma Technique through the journey of its implementation. Aditi Sunilkumar Ghosalkar "โSix Sigma Techniqueโ: A Journey Through its Implementation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64546.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64546/โsix-sigma-techniqueโ-a-journey-through-its-implementation/aditi-sunilkumar-ghosalkar
Edge Computing in Space Enhancing Data Processing and Communication for Space...ijtsrd
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Edge computing, a paradigm that involves processing data closer to its source, has gained significant attention for its potential to revolutionize data processing and communication in space missions. With the increasing complexity and data volume generated by modern space missions, traditional centralized computing approaches face challenges related to latency, bandwidth, and security. Edge computing in space, involving on board processing and analysis of data, offers promising solutions to these challenges. This paper explores the concept of edge computing in space, its benefits, applications, and future prospects in enhancing space missions. Manish Verma "Edge Computing in Space: Enhancing Data Processing and Communication for Space Missions" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64541.pdf Paper Url: https://www.ijtsrd.com/computer-science/artificial-intelligence/64541/edge-computing-in-space-enhancing-data-processing-and-communication-for-space-missions/manish-verma
Dynamics of Communal Politics in 21st Century India Challenges and Prospectsijtsrd
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Communal politics in India has evolved through centuries, weaving a complex tapestry shaped by historical legacies, colonial influences, and contemporary socio political transformations. This research comprehensively examines the dynamics of communal politics in 21st century India, emphasizing its historical roots, socio political dynamics, economic implications, challenges, and prospects for mitigation. The historical perspective unravels the intricate interplay of religious identities and power dynamics from ancient civilizations to the impact of colonial rule, providing insights into the evolution of communalism. The socio political dynamics section delves into the contemporary manifestations, exploring the roles of identity politics, socio economic disparities, and globalization. The economic implications section highlights how communal politics intersects with economic issues, perpetuating disparities and influencing resource allocation. Challenges posed by communal politics are scrutinized, revealing multifaceted issues ranging from social fragmentation to threats against democratic values. The prospects for mitigation present a multifaceted approach, incorporating policy interventions, community engagement, and educational initiatives. The paper conducts a comparative analysis with international examples, identifying common patterns such as identity politics and economic disparities. It also examines unique challenges, emphasizing Indias diverse religious landscape, historical legacy, and secular framework. Lessons for effective strategies are drawn from international experiences, offering insights into inclusive policies, interfaith dialogue, media regulation, and global cooperation. By scrutinizing historical epochs, contemporary dynamics, economic implications, and international comparisons, this research provides a comprehensive understanding of communal politics in India. The proposed strategies for mitigation underscore the importance of a holistic approach to foster social harmony, inclusivity, and democratic values. Rose Hossain "Dynamics of Communal Politics in 21st Century India: Challenges and Prospects" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64528.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/history/64528/dynamics-of-communal-politics-in-21st-century-india-challenges-and-prospects/rose-hossain
Assess Perspective and Knowledge of Healthcare Providers Towards Elehealth in...ijtsrd
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Background and Objective Telehealth has become a well known tool for the delivery of health care in Saudi Arabia, and the perspective and knowledge of healthcare providers are influential in the implementation, adoption and advancement of the method. This systematic review was conducted to examine the current literature base regarding telehealth and the related healthcare professional perspective and knowledge in the Kingdom of Saudi Arabia. Materials and Methods This systematic review was conducted by searching 7 databases including, MEDLINE, CINHAL, Web of Science, Scopus, PubMed, PsycINFO, and ProQuest Central. Studies on healthcare practitioners telehealth knowledge and perspectives published in English in Saudi Arabia from 2000 to 2023 were included. Boland directed this comprehensive review. The researchers examined each connected study using the AXIS tool, which evaluates cross sectional systematic reviews. Narrative synthesis was used to summarise and convey the data. Results Out of 1840 search results, 10 studies were included. Positive outlook and limited knowledge among providers were seen across trials. Healthcare professionals like telehealth for its ability to improve quality, access, and delivery, save time and money, and be successful. Age, gender, occupation, and work experience also affect health workers knowledge. In Saudi Arabia, healthcare professionals face inadequate expert assistance, patient privacy, internet connection concerns, lack of training courses, lack of telehealth understanding, and high costs while performing telemedicine. Conclusions Healthcare practitioners telehealth perceptions and knowledge were examined in this systematic study. Its collection of concerned experts different personal attitudes and expertise would help enhance telehealths implementation in Saudi Arabia, develop its healthcare delivery alternative, and eliminate frequent problems. Badriah Mousa I Mulayhi | Dr. Jomin George | Judy Jenkins "Assess Perspective and Knowledge of Healthcare Providers Towards Elehealth in Saudi Arabia: A Systematic Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64535.pdf Paper Url: https://www.ijtsrd.com/medicine/other/64535/assess-perspective-and-knowledge-of-healthcare-providers-towards-elehealth-in-saudi-arabia-a-systematic-review/badriah-mousa-i-mulayhi
The Impact of Digital Media on the Decentralization of Power and the Erosion ...ijtsrd
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The impact of digital media on the distribution of power and the weakening of traditional gatekeepers has gained considerable attention in recent years. The adoption of digital technologies and the internet has resulted in declining influence and power for traditional gatekeepers such as publishing houses and news organizations. Simultaneously, digital media has facilitated the emergence of new voices and players in the media industry. Digital medias impact on power decentralization and gatekeeper erosion is visible in several ways. One significant aspect is the democratization of information, which enables anyone with an internet connection to publish and share content globally, leading to citizen journalism and bypassing traditional gatekeepers. Another aspect is the disruption of conventional media industry business models, as traditional organizations struggle to adjust to the decrease in advertising revenue and the rise of digital platforms. Alternative business models, such as subscription models and crowdfunding, have become more prevalent, leading to the emergence of new players. Overall, the impact of digital media on the distribution of power and the weakening of traditional gatekeepers has brought about significant changes in the media landscape and the way information is shared. Further research is required to fully comprehend the implications of these changes and their impact on society. Dr. Kusum Lata "The Impact of Digital Media on the Decentralization of Power and the Erosion of Traditional Gatekeepers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64544.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/political-science/64544/the-impact-of-digital-media-on-the-decentralization-of-power-and-the-erosion-of-traditional-gatekeepers/dr-kusum-lata
Online Voices, Offline Impact Ambedkars Ideals and Socio Political Inclusion ...ijtsrd
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This research investigates the nexus between online discussions on Dr. B.R. Ambedkars ideals and their impact on social inclusion among college students in Gurugram, Haryana. Surveying 240 students from 12 government colleges, findings indicate that 65 actively engage in online discussions, with 80 demonstrating moderate to high awareness of Ambedkars ideals. Statistically significant correlations reveal that higher online engagement correlates with increased awareness p 0.05 and perceived social inclusion. Variations across colleges and a notable effect of college type on perceived social inclusion highlight the influence of contextual factors. Furthermore, the intersectional analysis underscores nuanced differences based on gender, caste, and socio economic status. Dr. Kusum Lata "Online Voices, Offline Impact: Ambedkar's Ideals and Socio-Political Inclusion - A Study of Gurugram District" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64543.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/political-science/64543/online-voices-offline-impact-ambedkars-ideals-and-sociopolitical-inclusion--a-study-of-gurugram-district/dr-kusum-lata
Problems and Challenges of Agro Entreprenurship A Studyijtsrd
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Noting calls for contextualizing Agro entrepreneurs problems and challenges of the agro entrepreneurs and for greater attention to the Role of entrepreneurs in agro entrepreneurship research, we conduct a systematic literature review of extent research in agriculture entrepreneurship to overcome the study objectives of complications of agro entrepreneurs through various factors, Development of agriculture products is a key factor for the overall economic growth of agro entrepreneurs Agro Entrepreneurs produces firsthand large scale employment, utilizes the labor and natural resources, This research outlines the problems of Weather and Soil Erosions, Market price fluctuation, stimulates labor cost problems, reduces concentration of Price volatility, Dependency on Intermediaries, induces Limited Bargaining Power, and Storage and Transportation Costs. This paper mainly devoted to highlight Problems and challenges faced for the sustainable of Agro Entrepreneurs in India. Vinay Prasad B "Problems and Challenges of Agro Entreprenurship - A Study" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64540.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64540/problems-and-challenges-of-agro-entreprenurship--a-study/vinay-prasad-b
Comparative Analysis of Total Corporate Disclosure of Selected IT Companies o...ijtsrd
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Disclosure is a process through which a business enterprise communicates with external parties. A corporate disclosure is communication of financial and non financial information of the activities of a business enterprise to the interested entities. Corporate disclosure is done through publishing annual reports. So corporate disclosure through annual reports plays a vital role in the life of all the companies and provides valuable information to investors. The basic objectives of corporate disclosure is to give a true and fair view of companies to the parties related either directly or indirectly like owner, government, creditors, shareholders etc. in the companies act, provisions have been made about mandatory and voluntary disclosure. The IT sector in India is rapidly growing, the trend to invest in the IT sector is rising and employment opportunities in IT sectors are also increasing. Therefore the IT sector is expected to have fair, full and adequate disclosure of all information. Unfair and incomplete disclosure may adversely affect the entire economy. A research study on disclosure practices of IT companies could play an important role in this regard. Hence, the present research study has been done to study and review comparative analysis of total corporate disclosure of selected IT companies of India and to put forward overall findings and suggestions with a view to increase disclosure score of these companies. The researcher hopes that the present research study will be helpful to all selected Companies for improving level of corporate disclosure through annual reports as well as the government, creditors, investors, all business organizations and upcoming researcher for comparative analyses of level of corporate disclosure with special reference to selected IT companies. Dr. Vaibhavi D. Thaker "Comparative Analysis of Total Corporate Disclosure of Selected IT Companies of India" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64539.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64539/comparative-analysis-of-total-corporate-disclosure-of-selected-it-companies-of-india/dr-vaibhavi-d-thaker
The Impact of Educational Background and Professional Training on Human Right...ijtsrd
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This study investigated the impact of educational background and professional training on human rights awareness among secondary school teachers in the Marathwada region of Maharashtra, India. The key findings reveal that higher levels of education, particularly a masterโs degree, and fields of study related to education, humanities, or social sciences are associated with greater human rights awareness among teachers. Additionally, both pre service teacher training and in service professional development programs focused on human rights education significantly enhance teacherโs knowledge, skills, and competencies in promoting human rights principles in their classrooms. Baig Ameer Bee Mirza Abdul Aziz | Dr. Syed Azaz Ali Amjad Ali "The Impact of Educational Background and Professional Training on Human Rights Awareness among Secondary School Teachers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64529.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/64529/the-impact-of-educational-background-and-professional-training-on-human-rights-awareness-among-secondary-school-teachers/baig-ameer-bee-mirza-abdul-aziz
A Study on the Effective Teaching Learning Process in English Curriculum at t...ijtsrd
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โOne Language sets you in a corridor for life. Two languages open every door along the wayโ Frank Smith English as a foreign language or as a second language has been ruling in India since the period of Lord Macaulay. But the question is how much we teach or learn English properly in our culture. Is there any scope to use English as a language rather than a subject How much we learn or teach English without any interference of mother language specially in the classroom teaching learning scenario in West Bengal By considering all these issues the researcher has attempted in this article to focus on the effective teaching learning process comparing to other traditional strategies in the field of English curriculum at the secondary level to investigate whether they fulfill the present teaching learning requirements or not by examining the validity of the present curriculum of English. The purpose of this study is to focus on the effectiveness of the systematic, scientific, sequential and logical transaction of the course between the teachers and the learners in the perspective of the 5Es programme that is engage, explore, explain, extend and evaluate. Sanchali Mondal | Santinath Sarkar "A Study on the Effective Teaching Learning Process in English Curriculum at the Secondary Level of West Bengal" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd62412.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/62412/a-study-on-the-effective-teaching-learning-process-in-english-curriculum-at-the-secondary-level-of-west-bengal/sanchali-mondal
The Role of Mentoring and Its Influence on the Effectiveness of the Teaching ...ijtsrd
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This paper reports on a study which was conducted to investigate the role of mentoring and its influence on the effectiveness of the teaching of Physics in secondary schools in the South West Region of Cameroon. The study adopted the convergent parallel mixed methods design, focusing on respondents in secondary schools in the South West Region of Cameroon. Both quantitative and qualitative data were collected, analysed separately, and the results were compared to see if the findings confirm or disconfirm each other. The quantitative analysis found that majority of the respondents 72 of Physics teachers affirmed that they had more experienced colleagues as mentors to help build their confidence, improve their teaching, and help them improve their effectiveness and efficiency in guiding learnersโ achievements. Only 28 of the respondents disagreed with these statements. With majority respondents 72 agreeing with the statements, it implies that in most secondary schools, experienced Physics teachers act as mentors to build teachersโ confidence in teaching and improving studentsโ learning. The interview qualitative data analysis summarized how secondary school Principals use meetings with mentors and mentees to promote mentorship in the school milieu. This has helped strengthen teachersโ classroom practices in secondary schools in the South West Region of Cameroon. With the results confirming each other, the study recommends that mentoring should focus on helping teachers employ social interactions and instructional practices feedback and clarity in teaching that have direct measurable impact on studentsโ learning achievements. Andrew Ngeim Sumba | Frederick Ebot Ashu | Peter Agborbechem Tambi "The Role of Mentoring and Its Influence on the Effectiveness of the Teaching of Physics in Secondary Schools in the South West Region of Cameroon" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64524.pdf Paper Url: https://www.ijtsrd.com/management/management-development/64524/the-role-of-mentoring-and-its-influence-on-the-effectiveness-of-the-teaching-of-physics-in-secondary-schools-in-the-south-west-region-of-cameroon/andrew-ngeim-sumba
Design Simulation and Hardware Construction of an Arduino Microcontroller Bas...ijtsrd
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This study primarily focuses on the design of a high side buck converter using an Arduino microcontroller. The converter is specifically intended for use in DC DC applications, particularly in standalone solar PV systems where the PV output voltage exceeds the load or battery voltage. To evaluate the performance of the converter, simulation experiments are conducted using Proteus Software. These simulations provide insights into the input and output voltages, currents, powers, and efficiency under different state of charge SoC conditions of a 12V,70Ah rechargeable lead acid battery. Additionally, the hardware design of the converter is implemented, and practical data is collected through operation, monitoring, and recording. By comparing the simulation results with the practical results, the efficiency and performance of the designed converter are assessed. The findings indicate that while the buck converter is suitable for practical use in standalone PV systems, its efficiency is compromised due to a lower output current. Chan Myae Aung | Dr. Ei Mon "Design Simulation and Hardware Construction of an Arduino-Microcontroller Based DC-DC High-Side Buck Converter for Standalone PV System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64518.pdf Paper Url: https://www.ijtsrd.com/engineering/mechanical-engineering/64518/design-simulation-and-hardware-construction-of-an-arduinomicrocontroller-based-dcdc-highside-buck-converter-for-standalone-pv-system/chan-myae-aung
Sustainable Energy by Paul A. Adekunte | Matthew N. O. Sadiku | Janet O. Sadikuijtsrd
ย
Energy becomes sustainable if it meets the needs of the present without compromising the ability of future generations to meet their own needs. Some of the definitions of sustainable energy include the considerations of environmental aspects such as greenhouse gas emissions, social, and economic aspects such as energy poverty. Generally far more sustainable than fossil fuel are renewable energy sources such as wind, hydroelectric power, solar, and geothermal energy sources. Worthy of note is that some renewable energy projects, like the clearing of forests to produce biofuels, can cause severe environmental damage. The sustainability of nuclear power which is a low carbon source is highly debated because of concerns about radioactive waste, nuclear proliferation, and accidents. The switching from coal to natural gas has environmental benefits, including a lower climate impact, but could lead to delay in switching to more sustainable options. โCarbon capture and storageโ can be built into power plants to remove the carbon dioxide CO2 emissions, but this technology is expensive and has rarely been implemented. Leading non renewable energy sources around the world is fossil fuels, coal, petroleum, and natural gas. Nuclear energy is usually considered another non renewable energy source, although nuclear energy itself is a renewable energy source, but the material used in nuclear power plants is not. The paper addresses the issue of sustainable energy, its attendant benefits to the future generation, and humanity in general. Paul A. Adekunte | Matthew N. O. Sadiku | Janet O. Sadiku "Sustainable Energy" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64534.pdf Paper Url: https://www.ijtsrd.com/engineering/electrical-engineering/64534/sustainable-energy/paul-a-adekunte
Concepts for Sudan Survey Act Implementations Executive Regulations and Stand...ijtsrd
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This paper aims to outline the executive regulations, survey standards, and specifications required for the implementation of the Sudan Survey Act, and for regulating and organizing all surveying work activities in Sudan. The act has been discussed for more than 5 years. The Land Survey Act was initiated by the Sudan Survey Authority and all official legislations were headed by the Sudan Ministry of Justice till it was issued in 2022. The paper presents conceptual guidelines to be used for the Survey Act implementation and to regulate the survey work practice, standardizing the field surveys, processing, quality control, procedures, and the processes related to survey work carried out by the stakeholders and relevant authorities in Sudan. The conceptual guidelines are meant to improve the quality and harmonization of geospatial data and to aid decision making processes as well as geospatial information systems. The established comprehensive executive regulations will govern and regulate the implementation of the Sudan Survey Geomatics Act in all surveying and mapping practices undertaken by the Sudan Survey Authority SSA and state local survey departments for public or private sector organizations. The targeted standards and specifications include the reference frame, projection, coordinate systems, and the guidelines and specifications that must be followed in the field of survey work, processes, and mapping products. In the last few decades, there has been a growing awareness of the importance of geomatics activities and measurements on the Earths surface in space and time, together with observing and mapping the changes. In such cases, data must be captured promptly, standardized, and obtained with more accuracy and specified in much detail. The paper will also highlight the current situation in Sudan, the degree to which survey standards are used, the problems encountered, and the errors that arise from not using the standards and survey specifications. Kamal A. A. Sami "Concepts for Sudan Survey Act Implementations - Executive Regulations and Standards" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63484.pdf Paper Url: https://www.ijtsrd.com/engineering/civil-engineering/63484/concepts-for-sudan-survey-act-implementations--executive-regulations-and-standards/kamal-a-a-sami
Towards the Implementation of the Sudan Interpolated Geoid Model Khartoum Sta...ijtsrd
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The discussions between ellipsoid and geoid have invoked many researchers during the recent decades, especially during the GNSS technology era, which had witnessed a great deal of development but still geoid undulation requires more investigations. To figure out a solution for Sudans local geoid, this research has tried to intake the possibility of determining the geoid model by following two approaches, gravimetric and geometrical geoid model determination, by making use of GNSS leveling benchmarks at Khartoum state. The Benchmarks are well distributed in the study area, in which, the horizontal coordinates and the height above the ellipsoid have been observed by GNSS while orthometric heights were carried out using precise leveling. The Global Geopotential Model GGM represented in EGM2008 has been exploited to figure out the geoid undulation at the benchmarks in the study area. This is followed by a fitting process, that has been done to suit the geoid undulation data which has been computed using GNSS leveling data and geoid undulation inspired by the EGM2008. Two geoid surfaces were created after the fitting process to ensure that they are identical and both of them could be counted for getting the same geoid undulation with an acceptable accuracy. In this respect, statistical operation played an important role in ensuring the consistency and integrity of the model by applying cross validation techniques splitting the data into training and testing datasets for building the geoid model and testing its eligibility. The geometrical solution for geoid undulation computation has been utilized by applying straightforward equations that facilitate the calculation of the geoid undulation directly through applying statistical techniques for the GNSS leveling data of the study area to get the common equation parameters values that could be utilized to calculate geoid undulation of any position in the study area within the claimed accuracy. Both systems were checked and proved eligible to be used within the study area with acceptable accuracy which may contribute to solving the geoid undulation problem in the Khartoum area, and be further generalized to determine the geoid model over the entire country, and this could be considered in the future, for regional and continental geoid model. Ahmed M. A. Mohammed. | Kamal A. A. Sami "Towards the Implementation of the Sudan Interpolated Geoid Model (Khartoum State Case Study)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63483.pdf Paper Url: https://www.ijtsrd.com/engineering/civil-engineering/63483/towards-the-implementation-of-the-sudan-interpolated-geoid-model-khartoum-state-case-study/ahmed-m-a-mohammed
Activating Geospatial Information for Sudans Sustainable Investment Mapijtsrd
ย
Sudan is witnessing an acceleration in the processes of development and transformation in the performance of government institutions to raise the productivity and investment efficiency of the government sector. The development plans and investment opportunities have focused on achieving national goals in various sectors. This paper aims to illuminate the path to the future and provide geospatial data and information to develop the investment climate and environment for all sized businesses, and to bridge the development gap between the Sudan states. The Sudan Survey Authority SSA is the main advisor to the Sudan Government in conducting surveying, mappings, designing, and developing systems related to geospatial data and information. In recent years, SSA made a strategic partnership with the Ministry of Investment to activate Geospatial Information for Sudans Sustainable Investment and in particular, for the preparation and implementation of the Sudan investment map, based on the directives and objectives of the Ministry of Investment MI in Sudan. This paper comes within the framework of activating the efforts of the Ministry of Investment to develop technical investment services by applying techniques adopted by the Ministry and its strategic partners for advancing investment processes in the country. Kamal A. A. Sami "Activating Geospatial Information for Sudan's Sustainable Investment Map" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63482.pdf Paper Url: https://www.ijtsrd.com/engineering/information-technology/63482/activating-geospatial-information-for-sudans-sustainable-investment-map/kamal-a-a-sami
Educational Unity Embracing Diversity for a Stronger Societyijtsrd
ย
In a rapidly changing global landscape, the importance of education as a unifying force cannot be overstated. This paper explores the crucial role of educational unity in fostering a stronger and more inclusive society through the embrace of diversity. By examining the benefits of diverse learning environments, the paper aims to highlight the positive impact on societal strength. The discussion encompasses various dimensions, from curriculum design to classroom dynamics, and emphasizes the need for educational institutions to become catalysts for unity in diversity. It highlights the need for a paradigm shift in educational policies, curricula, and pedagogical approaches to ensure that they are reflective of the diverse fabric of society. This paper also addresses the challenges associated with implementing inclusive educational practices and offers practical strategies for overcoming barriers. It advocates for collaborative efforts between educational institutions, policymakers, and communities to create a supportive ecosystem that promotes diversity and unity. Mr. Amit Adhikari | Madhumita Teli | Gopal Adhikari "Educational Unity: Embracing Diversity for a Stronger Society" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64525.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/64525/educational-unity-embracing-diversity-for-a-stronger-society/mr-amit-adhikari
Integration of Indian Indigenous Knowledge System in Management Prospects and...ijtsrd
ย
The diversity of indigenous knowledge systems in India is vast and can vary significantly between different communities and regions. Preserving and respecting these knowledge systems is crucial for maintaining cultural heritage, promoting sustainable practices, and fostering cross cultural understanding. In this paper, an overview of the prospects and challenges associated with incorporating Indian indigenous knowledge into management is explored. It is found that IIKS helps in management in many areas like sustainable development, tourism, food security, natural resource management, cultural preservation and innovation, etc. However, IIKS integration with management faces some challenges in the form of a lack of documentation, cultural sensitivity, language barriers legal framework, etc. Savita Lathwal "Integration of Indian Indigenous Knowledge System in Management: Prospects and Challenges" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63500.pdf Paper Url: https://www.ijtsrd.com/management/accounting-and-finance/63500/integration-of-indian-indigenous-knowledge-system-in-management-prospects-and-challenges/savita-lathwal
DeepMask Transforming Face Mask Identification for Better Pandemic Control in...ijtsrd
ย
The COVID 19 pandemic has highlighted the crucial need of preventive measures, with widespread use of face masks being a key method for slowing the viruss spread. This research investigates face mask identification using deep learning as a technological solution to be reducing the risk of coronavirus transmission. The proposed method uses state of the art convolutional neural networks CNNs and transfer learning to automatically recognize persons who are not wearing masks in a variety of circumstances. We discuss how this strategy improves public health and safety by providing an efficient manner of enforcing mask wearing standards. The report also discusses the obstacles, ethical concerns, and prospective applications of face mask detection systems in the ongoing fight against the pandemic. Dilip Kumar Sharma | Aaditya Yadav "DeepMask: Transforming Face Mask Identification for Better Pandemic Control in the COVID-19 Era" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64522.pdf Paper Url: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/64522/deepmask-transforming-face-mask-identification-for-better-pandemic-control-in-the-covid19-era/dilip-kumar-sharma
Streamlining Data Collection eCRF Design and Machine Learningijtsrd
ย
Efficient and accurate data collection is paramount in clinical trials, and the design of Electronic Case Report Forms eCRFs plays a pivotal role in streamlining this process. This paper explores the integration of machine learning techniques in the design and implementation of eCRFs to enhance data collection efficiency. We delve into the synergies between eCRF design principles and machine learning algorithms, aiming to optimize data quality, reduce errors, and expedite the overall data collection process. The application of machine learning in eCRF design brings forth innovative approaches to data validation, anomaly detection, and real time adaptability. This paper discusses the benefits, challenges, and future prospects of leveraging machine learning in eCRF design for streamlined and advanced data collection in clinical trials. Dhanalakshmi D | Vijaya Lakshmi Kannareddy "Streamlining Data Collection: eCRF Design and Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63515.pdf Paper Url: https://www.ijtsrd.com/biological-science/biotechnology/63515/streamlining-data-collection-ecrf-design-and-machine-learning/dhanalakshmi-d
THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...indexPub
ย
The recent surge in pro-Palestine student activism has prompted significant responses from universities, ranging from negotiations and divestment commitments to increased transparency about investments in companies supporting the war on Gaza. This activism has led to the cessation of student encampments but also highlighted the substantial sacrifices made by students, including academic disruptions and personal risks. The primary drivers of these protests are poor university administration, lack of transparency, and inadequate communication between officials and students. This study examines the profound emotional, psychological, and professional impacts on students engaged in pro-Palestine protests, focusing on Generation Z's (Gen-Z) activism dynamics. This paper explores the significant sacrifices made by these students and even the professors supporting the pro-Palestine movement, with a focus on recent global movements. Through an in-depth analysis of printed and electronic media, the study examines the impacts of these sacrifices on the academic and personal lives of those involved. The paper highlights examples from various universities, demonstrating student activism's long-term and short-term effects, including disciplinary actions, social backlash, and career implications. The researchers also explore the broader implications of student sacrifices. The findings reveal that these sacrifices are driven by a profound commitment to justice and human rights, and are influenced by the increasing availability of information, peer interactions, and personal convictions. The study also discusses the broader implications of this activism, comparing it to historical precedents and assessing its potential to influence policy and public opinion. The emotional and psychological toll on student activists is significant, but their sense of purpose and community support mitigates some of these challenges. However, the researchers call for acknowledging the broader Impact of these sacrifices on the future global movement of FreePalestine.
Andreas Schleicher presents PISA 2022 Volume III - Creative Thinking - 18 Jun...EduSkills OECD
ย
Andreas Schleicher, Director of Education and Skills at the OECD presents at the launch of PISA 2022 Volume III - Creative Minds, Creative Schools on 18 June 2024.
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
ย
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumMJDuyan
ย
(๐๐๐ ๐๐๐) (๐๐๐ฌ๐ฌ๐จ๐ง ๐)-๐๐ซ๐๐ฅ๐ข๐ฆ๐ฌ
๐๐ข๐ฌ๐๐ฎ๐ฌ๐ฌ ๐ญ๐ก๐ ๐๐๐ ๐๐ฎ๐ซ๐ซ๐ข๐๐ฎ๐ฅ๐ฎ๐ฆ ๐ข๐ง ๐ญ๐ก๐ ๐๐ก๐ข๐ฅ๐ข๐ฉ๐ฉ๐ข๐ง๐๐ฌ:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
๐๐ฑ๐ฉ๐ฅ๐๐ข๐ง ๐ญ๐ก๐ ๐๐๐ญ๐ฎ๐ซ๐ ๐๐ง๐ ๐๐๐จ๐ฉ๐ ๐จ๐ ๐๐ง ๐๐ง๐ญ๐ซ๐๐ฉ๐ซ๐๐ง๐๐ฎ๐ซ:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
Level 3 NCEA - NZ: A Nation In the Making 1872 - 1900 SML.pptHenry Hollis
ย
The History of NZ 1870-1900.
Making of a Nation.
From the NZ Wars to Liberals,
Richard Seddon, George Grey,
Social Laboratory, New Zealand,
Confiscations, Kotahitanga, Kingitanga, Parliament, Suffrage, Repudiation, Economic Change, Agriculture, Gold Mining, Timber, Flax, Sheep, Dairying,
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the bodyโs response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
Gait Recognition for Person Identification using Statistics of SURF
1. International Journal of Trend in Scientific Research and Development (IJTSRD)
Volume 3 Issue 5, August 2019 Available Online: www.ijtsrd.com e-ISSN: 2456 โ 6470
@ IJTSRD | Unique Paper ID โ IJTSRD26609 | Volume โ 3 | Issue โ 5 | July - August 2019 Page 1415
Gait Recognition for Person Identification
using Statistics of SURF
Khaing Zarchi Htun1, Sai Maung Maung Zaw2
1Research and Development Image Processing Lab, 2Faculty of Computer System and Technologies
1,2University of Computer Studies, Mandalay (UCSM), Mandalay, Myanmar
How to cite this paper: Khaing Zarchi
Htun | Sai Maung Maung Zaw "Gait
Recognition for Person Identification
using Statistics of
SURF" Published in
International
Journal of Trend in
Scientific Research
and Development
(ijtsrd), ISSN: 2456-
6470, Volume-3 |
Issue-5, August 2019, pp.1415-1422,
https://doi.org/10.31142/ijtsrd26609
Copyright ยฉ 2019 by author(s) and
International Journal ofTrend inScientific
Research and Development Journal. This
is an Open Access article distributed
under the terms of
the Creative
Commons Attribution
License (CC BY 4.0)
(http://creativecommons.org/licenses/by
/4.0)
ABSTRACT
In recent years, the use of gait for human identification is a new biometric
technology intended to play an increasingly important role in visual
surveillance applications. Gait is a less unobtrusive biometricrecognitionthat
it identifies people from a distance without any interaction or cooperation
with the subject. However, the effects of โcovariates factorsโ such as changes
in viewing angles, shoe styles, walking surfaces, carrying conditions, and
elapsed time make gait recognition problems more challenging for research.
Therefore, discriminative features extraction process from video frame
sequences is challenging. This system proposes statistical gait features on
Speeded-Up Robust Features (SURF) to represent the biometric gait feature
for human identification. This system chooses the most suitable gait features
to diminish the effects of โcovariate factorsโ so human identification accuracy
is effectiveness. Support Vector Machine (SVM) classifier evaluated the
discriminatory ability of gait pattern classification on CASIA-B (Multi-view
Gait Dataset).
KEYWORDS: Speed Up Robust Feature (SURF); Gait Recognition; Statistical Gait
Feature; Support Vector Machine (SVM)
I. INTRODUCTION
Biometrics is a study that automatically identifies people who use unique
physical or behavioral characteristics.
An individual's biometric identification distinguishes
individuals focused on their physical or behavioral
characteristics such as voice, face, gait, fingerprint and iris.
[1] Biometrics is becoming more and more important today
and is widely accepted because it is unique and will not be
lost over time. An individual's biometric identification
distinguishesindividualscenteredontheirbehavioraland/or
physical characteristics for example fingerprint, voice, face,
gait and iris. These two biometric technologies are broadly
used in forensics, safety, clinical analysis, monitoring and
other applications area.
In essence, gait recognition can be separated into two broad
groups: model-based methods and model-free. [2] Model-
based methods typically simulatethestructureandmotionof
the human body and highlight features to match the
components of the model.
Model-free approachfocusesoneithershapeofsilhouettesor
the whole motion of human bodies. The method without the
model focuses on both the shape of the contour and the
motion of the entire human body. In this way, the largest
connected area in the foreground of the image is considered
to be the contour of the human body. [3] It is insensitive to
contour quality and has lower computational costs than
model methods.
The proposed method is centered on statistical gait features
extracted result of Speeded Up Robust Features (SURF) from
the binary image, roughness image and gray scale image.
Feature extraction method is selected discriminating gait
features from three different images to get the high
recognition accuracy results for intra-class variation.
Evaluating the performance of the proposed system is
constructed on the Correct Classification Rate (CCR) of
CASIA-B gait database. In this paper, in order to exceed these
limitations, we propose a new gait features to identify the
human body by changing the conditions of the clothes,
carrying condition or varying the angle of view.
II. RELATED WORK
In the earlier period, several gait recognition approaches
have been proposed for human identification it can be
separated into two broad groups such as model-based and
model-freeapproach. Model-based approach that applicable
for human models and uses gait parameters thatareupdated
over time to represent gait. [4] Model-free approach using
motion information extracted directly from the silhouette.
Recent studies on gait recognition seem to prefer methods
model-free, mainly because of better performance than
model-based methods, as well as noise immunity and low
computational costs.
Johnson and Bobick (2001) proposed a multi-view gait
recognition method for gait recognition. Static body
parameters consider as the measurements taken from the
static gait frames.[5] They use walking action to extract
relative body parameters and do not directly evaluate based
IJTSRD26609
2. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID โ IJTSRD26609 | Volume โ 3 | Issue โ 5 | July - August 2019 Page 1416
dynamic gait patterns. The static parameters as height, the
distance between head and pelvis, the maximum distance
between pelvis and feet, and the distance between the feet.
The view invariant is static body parameters which
appropriate for recognition.
Lee and Grimson (2002) described the gaitsilhouettesdivide
into seven regions. [6] Each regionfittedwithellipsesandthe
centroid, aspect ratio of major and minor axis of the ellipse
and the orientation of major axis of the ellipse take as gait
parameters these extracted as features from each region.
From all the silhouettes of a gait cycle extracted gait features
these were well organized andwereusedforgaitrecognition.
F. Tafazzoli and R. Safabakhsh (2010) proposed the shape
model divides thesubject's bodyintothreeregions:thetorso,
the head,and the extremitiestoobtainstaticparameterssuch
as body size, center of gravity coordinates, and gait cycle. [7]
The motion model consists of four parts: the head, the torso,
the legs and the arms, used to estimate dynamic parameters.
The method uses an active contour model to determine the
boundaries of each limb. Each limb is modeled as two canes,
representing the thighs and together with the tibia at the
knee joint and their rotational models form a dynamic
walking function. The dynamic Hough transform is used to
study the effects of weaponry on gait detection using NNC.
Jasmine Anitha and S. M. Deepa (2014) Video tracking is the
process of using a camera to position a moving object (or
multiple objects) over time. The algorithm analyzes
consecutive video frames as the video is being tracked. [8]
They described combine algorithm to improve the tracking
efficiency by using SURF descriptor with Harris corner
detector. The SURF function descriptor works by reducing
the search space of possible points of interest within the
pyramid of largescale spatial images.Usethecornerdetector
to locate interesting points in the image. Using the Harris
angle algorithm along the SURF function descriptor can
improve tracking efficiency.
C. BenAbdelkader et al., (2002) [9] used the model-free
method in calculates the gait phase of an object by analyzing
the width of the bounding box enclosing the motion contour
surrounding the silhouette of subject, and uses a Bayesian
classification to confirm the identity of the subject. However,
the silhouette width isnotsuitableforcalculatingtherunning
time of the front view of a moving object.
L. Wang et al., (2003) used contour unwrapping silhouette
centroid to convert a binary silhouette into a 1-dimensional
(1D) normalized distance signal. [10] Principal component
analysis (PCA) is used to reduce the dimensional of the
feature space. Centroid obtained in the eigenspace
transformation based on Principal Component Analysis
(PCA). To increase the identification accuracy based on the
subjectโs physical parameters.]
Ait O Lishani and Larbi Boubchir (2017) proposed a
supervised feature extraction method that selects unique
features to identify human gait under carrying and clothing
situations, thereby effective recognition performance. [11]
The characteristics of Haralick take out from the gait energy
image (GEI). The proposed method is based on the Haralick
features locally selected from the equal regions of the GEI,
using the RELIEF selectionalgorithmforextractingtheobject
to select only the most important objects with the least
redundancy. Proposed method evaluated on the CASIA gait
database (dataset B) based on changes in clothing and
wearing conditions from different perspectives, and
experimental results by the KNN classifier with effective
results over 80%.
Therefore, this paper presents more effective feature
extraction method to extract distinct statistical gait features
created on the outcomesofSpeedUpRobustFeatures(SURF)
descriptor. Human silhouette image extracted from the
background image by means of framedifferencebackground
subtraction technique. SURF features described as basic
features by using SURF descriptor from silhouette image.
Finally, the propose features are extracted the outcomes of
SURF from three different types of image: binary image,
roughness image and gray scale image for this identification
system.
Finally,tenfoldscross-validationsareverifiedontheCASIA-B
dataset ten times to get new results.Datasetisseparatedinto
ten subsets andcross-validationisseparatedintotensubsets.
Each validation period subgroup is nine training set, and the
remaining one is a testing set.After executing this validation,
it orders exact measurement of the classification accuracy.
Support Vector machine (SVM) classifier applied for
proposed system as a result of its advanced identification
accuracy.
The remainder of this paper: Part III is a review of the
proposed system. Section IV provides a detailed description
of the gait recognition process and describes the proposed
features. Thefinalsectiondescribesdetailanalysisofpropose
gait-based identification system. The propose feature is very
simple, so it can significantly recognize the gait feature for
identifying person.
III. THE PROPOSED SYSTEM OVERVIEW
Firstly, the proposed system is detected foregroundimageor
moving object from the background section on the input
video. In background subtraction step silhouette image is
acquired by subtracting the binary person frame from the
binary background frame. It reduces less memory space and
execution time. The second step consists of two phases that
are the interest point detection and description for three
different images. In the first phase, for each interest points,
SURF detector detect image and then return collection of
interest points. For each interest point, the descriptor
calculate feature vector to describe the surround region of
each point in second phase. These two phases require re-
computing the entire image.
For feature extraction step, this system is proposed
discriminating twelve statisticalgaitfeaturescomputedfrom
the results SURF descriptor of Binary image (BW),
Roughness(R) and Gray (G) image under carrying bag and
wearing conditions over eleven various view angles to
increase the recognition performance.
These twelve statistical gait features are Mean (BW), Root
Mean Square(RmsBW), Skewness (SkBW),Kurtosis(KuBW),
Mean(R), Root Mean Square (RmsR), Skewness (SkR),
Kurtosis (KuR), Mean (G), Root Mean Square (RmsG),
Skewness (SkG), Kurtosis (KuG). Finally the extracted gait
signals are comparing with gait signals that are stored in a
database. Support Vector Machine (SVM) is suitable to
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examine the capabilityoftheextractedstatisticalgaiteatures.
The flow of the system outline is displayed in Figure.1.
Figure-1: Overview of the Proposed System
IV. PROPOSED SYSTEM
Human identification based on gait recognition has become
an attractive research area in computer vision, video
surveillance and healthcare system. This system presents
model-free approach to extract statistical gait features from
the SURF feature descriptor results. The proposed system
selects the significant features for human recognition to
reduce the influence of intra-class variation in order to
increase recognition performance.
A. Moving Object Detection And Silhouette Extraction
The first step of proposed system used frame difference
background subtraction method to extract the silhouette
images. This method detects andextractsmovingobjectfrom
the background scene foreachframeofinputvideosequence.
In this step, original imageis convertedtobinaryimageusing
threadsholding level 0.3 for person frame and 0.25 for
background frame. Silhouette image is acquired from the
binary person frame is subtracted from the binary
background frame. The noise and small objects remove from
the binary image to get the human silhouette image
successively.Backgroundsubtractionmethodeasilyadaptsto
the changing background compared with the other methods.
This figure shows silhouette images for input video
sequence.
Figure-2: Example of Human Silhouette or Foreground
Image
A binary image is a digital image that has only two probable
values for every pixel. Generally, the two colors used for
binary images are black and white.Thecolorused forobjects
in the image is the foreground color, and the remaining
images are the background colors. Binary image (BW) get
from the person binary image subtract from the background
binary image.
Waviness is the measurement of the more widely spaced
component of roughness image. Roughness measured the
intensity difference between the pixels and it used to extract
distinct features. Waviness and Roughnessimagearevertical
distribution of pixel values of the image.Wavinessimage(W)
acquires by convolution with the binary image (BW) and
Gaussian filter. Roughness image(R) acquiresfromwaviness
image subtract from the binary image (BW). RGB image
acquires by masking BW image on original image and this
RGB image is converted into gray scale image (G) ) by
forming a weighted sum of the Red (R), Green (G)
and Blue(B) components: 0.2989 * R + 0.5870 * G + 0.1140 *
B.
Figure-3: Binary, Roughness and Gray Scale Images
B. Interest Point Detection
SURF algorithm is used to increase the gait recognition
system performance. First, the SURF detector is used to find
interest feature points in image, and the descriptorretrieves
feature vectors for each point of interest. SURF usedIntegral
image technique to overcome the size invariant.
The detection phase uses Hessian-matrix to detect the same
points of interest at different scales. [12] Integral image is
used to store addition of every pixels intensity value from
the input image within rectangular area between point and
original image. The formula for integral image is:
(1)
After calculating the integral image, only three operations
(subtraction or addition) are needed to compute the sum of
the pixel intensities on any vertical rectangular region
unrestricted of its size. This figure shows the integral image
from input image.
Figure-4: Integral Image for Input Image
As a result of a box filter and an integralimage,SURF directly
changes the box filter ratio to achieve a relative space. [12]
In image I, a point p = (x, y) is defined by Hessian matrixH(x,
ฯ) in x at scale ฯ:
๏ฅ๏ฅ
๏ฃ
๏ฝ
๏ฃ
๏ฝ
๏ฝ๏ฅ
xi
i
yj
j
jiIXI
0 0
),()(
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๐ป(๐, ๐) =
๐ฟ (๐, ๐) ๐ฟ (๐, ๐)
๐ฟ (๐, ๐) ๐ฟ (๐, ๐)
(2)
Where Laplacian of Gaussian Lxx (p, ฯ) is the convolution
Gaussian second order derivative ๐(๐) with the image I
in point p and also for Lxy (p,ฯ), Lyy (p,ฯ). These interest
points are used in human silhouette image.
Figure-5: Visual Representation for Hessian matrix of
Input Image
Approximate Hessian-matrix is calculated find out distinct
interest points of image that is extremely fast because the
calculated Hessian matrix is based on the integral imageand
it reduces computational costand time.Hessiandeterminant
is used to define the interest point location with this
determent maxima value.
det โ = ๐ท ๐ท โ (๐๐ท ) (3)
Where Dxx is the horizontal response of the second
derivative block filter for a given center integral pixel, Dyy is
vertical filter response, and Dxy is the diagonal filter
response. Figure-6 shows visual approximated Hessian
matrix. [13] An approximation Gaussian box filter size 9ร9
with scale ฯ=1.2 is the bottom level (maximum spatial
resolution) for blob-response maps.
โ
approx
(๐, ๐) =
๐ท (๐, ๐) ๐ท (๐, ๐)
๐ท (๐, ๐) ๐ท (๐, ๐)
(4)
Where Dxx(p ,ฯ) , Dyy (p ,ฯ) and Dxy(p ,ฯ) are element of
approximated Hessian matrix and these are convolutions of
the approximated filters with image I respectively.
Figure-6: Visual illustration for finding element of the
approximated Hessian matrix (Dxx(x ,ฯ) , Dyy(x ,ฯ) and
Dxy(x ,ฯ)
The approximate matrix needed to resize a pyramidal scale
for matching the interest points across different scales. [14]
Each scale is defined as the image response convolved with a
box filters a certain dimension (9x9, 15x15, etc.). Octave
denotes a series of response maps or filters of covering a
doubling scale.
Figure-7: Mathematical representation for Response Map
of Scale Space Representation
Each response map consists of width, height, box filter scale,
filter size, responses and laplacian sign of image. Sign of
Laplacian (-1, 1) represented the dissimilarity between dark
spots found on a brightbackgroundversusbrightspotsfound
on a dark background. [15] After creation of responsemapin
different scale space, the next task is to locate the points of
interest.
In 3x3x3 region, non-maximumsuppressionis usedtolocate
and resize the points of interest of image.The process of
suppressinganon-maximumconsistsinfindinglocalmaxima
within about 8 pixels from itself, its upper and lower
response images. If the center pixel has the highest intensity
in the search area, it is treated as a local maximum. It then
compares the center pixel to a user-defined threshold to
exceed the threshold and assumes that the pixel is an
interesting point of the local maximum. The method can
determine points of interest with x, y (coordinates) andscale
only on the second and third layers in each octave.
The interest points are needed to interpolate to get the
correct scale and position because the interest points are
obtained from the different scale space of images. The
interpolation fornon-maximumsuppressionisusedtoadjust
scaleand space of these interestedpoints.Inessencewehave
to fit a 3D quadratic expressing the Hessian H(x;y;ฯ)byusing
a Taylor expansion for finding extreme by setting the
derivative to zero and solving the equation(5) to find x =
(x;y;ฯ):
H(x) = H + x + x x (5)
x = โ (6)
This derivative is calculated from finite differences in the
response maps to get correct positions and scale.
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Interested points
(x, y, scale)
Figure-8: Mathematical representation of interest points
with Scale and Laplacian for Input Image
Figure-8 shows number of interest points, scale and sign of
Laplacian form input human silhouette image.
C. Orientation Assignment
The SURF descriptordescribesthepixelintensitydistribution
in the vicinity of the point of interest. At this stage, the
orientation assignment is used to determine the value of the
direction for each object (rotation invariance). At the
sampling stage, size of Haar wavelets depends on the scale
and is set equal to the side length of 4s, and x, y and the scale
are displayed on the integral image for fast filtering. These
wavelet convolution filters are necessary to calculate six
operations based on an integral image in order to get
responses in the x and y directions at any scale.
The Haar wavelet responses or gradients are obtained by
convolution with a first-order wavelet filter and an integral
image in a circular region with radius 6 scales. Apply a
Gaussian weighting function to the Haar waveletresponse(ฯ
= 2s) to further emphasizethesamplecenterpoint.Toreduce
the effect of distant pixels, multiply the response of the Haar
wavelet's result by Gaussian kernel 2s (s= scale).
All of these Gaussian weighted responses arethenmappedto
the two-dimensional space using the x and y direction
responses. [16] The local orientation vector is estimated by
computing sum of all responses surrounded by the ฯ / 3 (or)
60 degree slide orientation window. Create a new object
vector by summing the horizontal and vertical responses of
all windows. Here, the longest vector(maximumvalue)isthe
main direction of the point of interest. Figure-9 and 10 show
the process of orientation assignment and value for location
of interest point and scale.
Figure-9: Orientation assignment: The ฯ/3 sliding window
determines the dominant direction of the Gaussian-
weighted Haar wavelet response at all points in the
circular neighborhood around the point of interest.
Figure-10: Orientation Assignment values for each interest
point using x, y, Scale and Laplacian
D. Feature Description
The next step of the proposed system is describing feature
vector by calculating the neighborhoodofeachinterestpoint.
The SURF descriptor is focused on the point of interestwitha
sampling step size of 20s and constitutes a square area
aligned with its direction to extract the feature. The area of
interest is separated into smaller 4x4 sub-areas. [17] For
every sub-region, the Haar wavelet response calculated at
5x5 regular intervals in the rotational direction is a 2s Haar
convolution wavelet filter. The Haar wavelet reduces
computation time and increases reliability, the size depends
on the scale of the function ฯ. The Haar horizontal and
vertical wavelet responses (dx and dy) are multiplied by a
Gaussian weight of 3.3 sigma using distance between every
pixel in the region and the center point to reduce the effects
of geometric deformations and localization errors. The
horizontal and vertical directions of the feature path can be
alternately rotated.
Figure-11: A 20s areas is divided into 4x4 subareas that
are sampled 5x5 times to get the wavelet response
Fi
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In the featuredescriptor abstraction, the first stepconsistsof
constructing a rectangular area towards the direction
determined by the method of centering on the interest point
and selecting the direction. [18]Thisareaseparatedinto4x4
small squares. This saves important spatial information. The
Haar wavelet response was calculated using 5 ร 5 aliquots in
each sub-region. Determine the directionofhorizontaldx and
vertical dy. These are the first set of records for each unique
vector. Thus, each subfield has a four dimensional vector
descriptor for its basic strength structure.
๐ฃ = (โ ๐๐ฅ , โ ๐๐ฆ , โ |๐๐ฅ| , โ |๐๐ฆ|) (7)
If all 4x4 sub-areas are related, final result is a 64-
dimensional vectordescriptor.Thisisusuallyusedinthenext
similar feature phase. These features distinct because of the
number and location of the points selected by the SURF
detector and SURF descriptor calculate the objects around
these points. Figure 12 shows the wavelet responses
computed for each square and figure 13 shows the results of
SURF features points from Binary image.
The green square limits any of the 16 sub-areas,andthe blue
circle indicates the sample pointwhichthewavelet response
should be calculated.
Figure-12: The wavelet responses computed for each
square. The 2x2 sub-partitions of each square correspond
to the actual descriptor fields. These are the sums dx, |dx|,
dy, and |dy| calculated relatively to the orientation grid.
Figure-13: 76 - SURF Features Points from Binary Image
E. Gait Features Extraction
The feature extraction procedure is defined as a collection of
features that provide important information efficiently or
prominently foranalysisandclassification.Featurespoints of
interest are used when extracting movement parameters
from a sequence of gait patterns to show patterns of a
personโs gait. The feature of point of interest is used when
the motion parameters are extracted from a sequenceofgait
patterns to display the gait pattern of the person.
In this paper, the SURF features are used as the basis
features for calculating the individual characteristics of
walking. These features extracted from a series of three
different type images are binary image,roughness image and
gray scale image. For this reason, points of location and the
number selected in the SURF detector are different in every
individual's image.
This system uses statistical measurement approach to
extract gait-specific features to identify people. Statistics is
the systematic collection and analysis of numerical data to
study the relationships between phenomena and to predict
and control their occurrence. There are various statistics
such as mean, mode, median, variance, standard deviation,
covariance, asymmetry and kurtosis. For the gait feature
extraction, twelve statistical gait features are Mean (BW),
Root Mean Square(RmsBW), Skewness (SkBW), Kurtosis
(KuBW), Mean(R), Root Mean Square (RmsR), Skewness
(SkR), Kurtosis (KuR), Mean (G), Root Mean Square (RmsG),
Skewness (SkG), Kurtosis (KuG) are used as gait features
these features are calculated from the result of SURF
descriptor. [19] Statistical measurements identify a valueas
a representation of the entire distribution. This allows all
data to be accurately described using a small number of
parameters.
Mean is a basic texture feature that represents the average
pixel value of the image. This type of calculation removes
random faults and supports to obtain precise result thanthe
result of a single experiment.
๐๐๐๐ =
ร
โ โ ๐ฅ (8)
The standard deviation is the root mean square value of the
deviation from the average of the underlying texture.
๐ ๐๐ =
ร
โ โ |๐ฅ โ ๐ฅ | (9)
Kurtosis and Skewness are called "shape" statistics. That is,
they represent the shape of the pixel value distribution.
๐๐ =
ร
โ โ |๐ฅ โ ๐ฅ | (10)
๐พ๐ข =
ร
โ โ |๐ฅ โ ๐ฅ | (11)
where m, n are number of rows and columns ofSURFfeature
matrix, xm mean of average feature vector value from SURF
feature matrix and xij mean of feature vector value at i,j
coordinate from SURF feature matrix. Figure 14 shows
proposed statistical gait features for one person.
Figure 14: Proposed Statistical Gait Features for One
Person
F. Support Vector Machine (SVM)
Recently, Support Vector Machines (SVM) has become a
powerful classification method in several research fields.
This statistical machine learning technique was first
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introduced by Vapnik in 1995 [19]. This algorithm prevents
redefinition by choosing a specific hyperplane from a set of
data that can be shared in the feature space. The SVM uses a
linear segmentation hyperplane to create a classifier to
maximize margins. The width of the field between periods is
considered an optimization criterion. The margin is defined
as the distance between the nearest points of the classroom
data the best hyperplane. Guillon, Boser, and Vapnik show
how to produce a nonlinear classifier by kernel functions in
the original input space during the 1992 nonlinear
separation. First, the SVM converts the original object into a
feature space. Various nonlinear mappings can be used to
obtain the transform. [20] The kernel function K(x;y) can be
selected according to the task. After this conversion,you can
easily find the best hyperplane. The achieved hyperplane is
the best case for maximum margin.
V. EXPERIMENTAL RESULT AND ANALYSIS
In this paper, CASIA provides multipleviewsofCASIA-Bdata.
CASIA-B dataset (several walking databases) consists of 124
subjects taken from eleven different view angles from 0 to
180 degrees. Every subject has two dressing sequences, two
carrying bag condition and six regular walking sequences.
Each frameis shot witha camera by a video resolutionof320
x 240 pixels and a frame rate of 25 frames per second. These
videos operate under different lighting conditions with
different covariate conditions (carrying luggage, wearing
coats, and changing vision), fast walking,normalwalkingand
slow walking speeds from different sides. People have 110
video clips, each containing more than 90 frames. The data
set contains 124 people and has 13,640 video0 sequences
with a disk size of approximately 17 GB. The proposed
method is tested on 11550 video sequences of 105 persons
with 11 different view angles. Experimental results display
that the proposed approach has the characteristics of high
recognition rate and strong robustness.
Ten-fold cross validation is used to classify in separating all
features into ten disconnect subgroups. Each disconnects
subgroup used for training and testing by performing cross-
validation. Cross-validation is used to verify human
perception at threshold 10. The proposed system estimation
centered on a support vector machine (SVM). This
classification provides best classification accuracy for all
types of walking in the class.
(a) Sevral videos sequence with eleven view variation
(b) Foreground images of different input video sequences
(c) SURF features points of different foreground images
TABLE I. PROPOSED FEATURES AND DESCRIPTIONS
Gait Features Descriptions
Proposed
Statistical
Features
based SURF
Mean (BW), Root Mean
Square(RmsBW), Skewness
(SkBW), Kurtosis (KuBW),
Mean(R), Root Mean Square
(RmsR), Skewness (SkR),
Kurtosis (KuR), Mean (G), Root
Mean Square (RmsG), Skewness
(SkG), Kurtosis (KuG).
Propose features are made using statistical values based on
the results of SURF, they are Mean (BW), Root Mean
Square(RmsBW), Skewness (SkBW), Kurtosis (KuBW),
Mean(R), Root Mean Square (RmsR), Skewness (SkR),
Kurtosis (KuR), Mean (G), Root Mean Square (RmsG),
Skewness (SkG), Kurtosis (KuG). Proposed statistical gait
features and their description shown in Table I.
TABLE II. PERSON IDENTIFICATION RESULTS
Propose
Features
and its
length
Total Number
of Video
Sequences
Average
Identification
Accuracy over 10-
Fold Cross
Validation (%) SVM
Statistic
Features
from SURF
(12)
1100 (10-
Persons)
85.6
5500 (50-
Persons)
68.4
11550 (105-
Persons)
62.6
In Table II, The propose features provided to identifypeople
with various intra-class variation (wearing coats, carrying
baggage and walking normally). This table shows correct
human identification rate of three covariate conditions with
different view angles.
TABLE III. CORRECT GAIT CLASSIFICATION RESULTS
Intra-class
Variation and
Gait Features
Length
Total
Number of
Video
Sequences
Average
Classification
Accuracy over 10-
Fold Cross
Validation (%) SVM
Carrying Bag
(12)
2508 (114-
Persons)
50.2
Wearing Coat
(12)
2332 (107-
Persons)
52.6
ormal Walking
(12)
7524 (114-
Persons)
82.5
Table III shows propose features classification results for
each covariate type (Carrying condition, dress and Normal
Walking with different speed) with eleven viewpoints. For
two carrying bags, the classification accuracy rate of 114
people is 50.2%. When wearing two coats, 52.6% of the
recognition accuracy was confirmed in 2332 video
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sequences (107 people). Under normal six walking
conditions, the video sequence tested at 7524 (114 people)
gave 82.5% SVM classification accuracy. In this table, the
accuracy of the covariate normal walking SVM classifier is
superior to other covariates and other classification
methods.
VI. CONCLUSION
This paper describes gait based on human recognition. The
propose system is appropriate for monitoring and security
areas. This system presents twelve statistical gait features
these are tested under three covariance factors with eleven
various view angles to obtain advanced discrimination
identification accuracy. The proposed feature is modest, the
person identification accuracy is appropriate, but it needs to
obtain the maximum gait classification accuracy, while
considering other important features. Further research will
focus on more effective method to extract gait features to
measure similarity and effective classifier.
ACKNOWLEDEDGMENT
The authors would like to thanks Institute of Automation,
Chinese Academy of Sciences (CASIA) for supporting the
datasets.
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