In the navigation system, the desired destination position plays an essential role since the path planning algorithms takes a current location and goal location as inputs as well as the map of the surrounding environment. The generated path from path planning algorithm is used to guide a user to his final destination. This paper presents a proposed algorithm based on RGB-D camera to predict the goal coordinates in 2D occupancy grid map for visually impaired people navigation system. In recent years, deep learning methods have been used in many object detection tasks. So, the object detection method based on convolution neural network method is adopted in the proposed algorithm. The measuring distance between the current position of a sensor and the detected object depends on the depth data that is acquired from RGB-D camera. Both of the object detected coordinates and depth data has been integrated to get an accurate goal location in a 2D map. This proposed algorithm has been tested on various real-time scenarios. The experiments results indicate to the effectiveness of the proposed algorithm.
Depth Estimation from Defocused Images: a SurveyIJAAS Team
An important step in 3D data generation is the generation of depth map. Depth map is a black and white image which has exactly the same size of the original captured 2D image that indicates the relative distance of each pixel from the observer to the objects in the real world. This paper presents a survey of Depth Perception from Defocused or blurs images as well as image from motion. The change of distance of the object from the camera has direct relation with the amount of blurring of object in the image. The amount of blurring will be calculated with a comparison in front of the camera directly and can be seen with the changes at gray level around the edges of objects.
An Assessment of Image Matching Algorithms in Depth EstimationCSCJournals
Computer vision is often used with mobile robot for feature tracking, landmark sensing, and obstacle detection. Almost all high-end robotics systems are now equipped with pairs of cameras arranged to provide depth perception. In stereo vision application, the disparity between the stereo images allows depth estimation within a scene. Detecting conjugate pair in stereo images is a challenging problem known as the correspondence problem. The goal of this research is to assess the performance of SIFT, MSER, and SURF, the well known matching algorithms, in solving the correspondence problem and then in estimating the depth within the scene. The results of each algorithm are evaluated and presented. The conclusion and recommendations for future works, lead towards the improvement of these powerful algorithms to achieve a higher level of efficiency within the scope of their performance.
Stereo Correspondence Algorithms for Robotic Applications Under Ideal And Non...CSCJournals
The use of visual information in real time applications such as in robotic pick, navigation, obstacle avoidance etc. has been widely used in many sectors for enabling them to interact with its environment. Robotics require computationally simpler and easy to implement stereo vision algorithms that will provide reliable and accurate results under real time constraint. Stereo vision is a less expensive, passive sensing technique, for inferring the three dimensional position of objects from two or more simultaneous views of a scene and there is no interference with other sensing devices if multiple robots are present in the same environment. Stereo correspondence aims at finding matching points in the stereo image pair based on Lambertian criteria to obtain disparity. The correspondence algorithm will provide high resolution disparity maps of the scene by comparing two views of the scene under the study. By using the principle of triangulation and with the help of camera parameters, depth information can be extracted from this disparity .Since the focus is on real-time application, only the local stereo correspondence algorithms are considered. A comparative study based on error and computational costs are done between two area based algorithms. Evaluation of Sum of absolute Difference algorithm, which is less computationally expensive, suitable for ideal lightening condition and a more accurate adaptive binary support window algorithm that can handle of non-ideal lighting conditions are taken for this study. To simplify the correspondence search, rectified stereo image pairs are used as inputs.
Depth Estimation from Defocused Images: a SurveyIJAAS Team
An important step in 3D data generation is the generation of depth map. Depth map is a black and white image which has exactly the same size of the original captured 2D image that indicates the relative distance of each pixel from the observer to the objects in the real world. This paper presents a survey of Depth Perception from Defocused or blurs images as well as image from motion. The change of distance of the object from the camera has direct relation with the amount of blurring of object in the image. The amount of blurring will be calculated with a comparison in front of the camera directly and can be seen with the changes at gray level around the edges of objects.
An Assessment of Image Matching Algorithms in Depth EstimationCSCJournals
Computer vision is often used with mobile robot for feature tracking, landmark sensing, and obstacle detection. Almost all high-end robotics systems are now equipped with pairs of cameras arranged to provide depth perception. In stereo vision application, the disparity between the stereo images allows depth estimation within a scene. Detecting conjugate pair in stereo images is a challenging problem known as the correspondence problem. The goal of this research is to assess the performance of SIFT, MSER, and SURF, the well known matching algorithms, in solving the correspondence problem and then in estimating the depth within the scene. The results of each algorithm are evaluated and presented. The conclusion and recommendations for future works, lead towards the improvement of these powerful algorithms to achieve a higher level of efficiency within the scope of their performance.
Stereo Correspondence Algorithms for Robotic Applications Under Ideal And Non...CSCJournals
The use of visual information in real time applications such as in robotic pick, navigation, obstacle avoidance etc. has been widely used in many sectors for enabling them to interact with its environment. Robotics require computationally simpler and easy to implement stereo vision algorithms that will provide reliable and accurate results under real time constraint. Stereo vision is a less expensive, passive sensing technique, for inferring the three dimensional position of objects from two or more simultaneous views of a scene and there is no interference with other sensing devices if multiple robots are present in the same environment. Stereo correspondence aims at finding matching points in the stereo image pair based on Lambertian criteria to obtain disparity. The correspondence algorithm will provide high resolution disparity maps of the scene by comparing two views of the scene under the study. By using the principle of triangulation and with the help of camera parameters, depth information can be extracted from this disparity .Since the focus is on real-time application, only the local stereo correspondence algorithms are considered. A comparative study based on error and computational costs are done between two area based algorithms. Evaluation of Sum of absolute Difference algorithm, which is less computationally expensive, suitable for ideal lightening condition and a more accurate adaptive binary support window algorithm that can handle of non-ideal lighting conditions are taken for this study. To simplify the correspondence search, rectified stereo image pairs are used as inputs.
Gesture Recognition Review: A Survey of Various Gesture Recognition AlgorithmsIJRES Journal
This paper presents simple as well as effective methods to realize hand gesture recognition. Gesture recognition is mainly apprehensive on analysing the functionality of human Intelligence. The main aim of gesture detection and recognition is to design an efficient system which is able to recognize particular human gestures and use these detected gestures to transfer information or for controlling devices. Hand gestures enable a vivid complementary modal to communicate with speech for expressing ones thought of idea. The information which is associated with hand gestures detection in a conversation is extent or degree, detection discourse structure, spatial and temporal design structure. Based on the above given points the paper discusses various models of gesture detection and recognition.
Digital 3D imaging can benefit from advances in VLSI technology in order to accelerate its deployment in many fields like visual communication and industrial automation. High-resolution 3D images can be acquired using laser-based vision systems. With this approach, the 3D information becomes relatively insensitive to background illumination and surface texture. Complete images of visible surfaces that are rather featureless to the human eye or a video camera can be generated. Intelligent digitizers will be capable of measuring accurately and simultaneously color and 3D.
This paper presents the maneuver of mouse pointer and performs various mouse operations such as left
click, right click, double click, drag etc using gestures recognition technique. Recognizing gestures is a
complex task which involves many aspects such as motion modeling, motion analysis, pattern recognition
and machine learning.
Keeping all the essential factors in mind a system has been created which recognizes the movement of
fingers and various patterns formed by them. Color caps have been used for fingers to distinguish it from
the background color such as skin color. Thus recognizing the gestures various mouse events have been
performed. The application has been created on MATLAB environment with operating system as windows
7.
Object Detection for Service Robot Using Range and Color Features of an ImageIJCSEA Journal
In real-world applications, service robots need to locate and identify objects in a scene. A range sensor provides a robust estimate of depth information, which is useful to accurately locate objects in a scene. On the other hand, color information is an important property for object recognition task. The objective of this paper is to detect and localize multiple objects within an image using both range and color features. The proposed method uses 3D shape features to generate promising hypotheses within range images and verifies these hypotheses by using features obtained from both range and color images.
Object detection for service robot using range and color features of an imageIJCSEA Journal
In real-world applications, service robots need to locate and identify objects in a scene. A range sensor
provides a robust estimate of depth information, which is useful to accurately locate objects in a scene. On
the other hand, color information is an important property for object recognition task. The objective of this
paper is to detect and localize multiple objects within an image using both range and color features. The
proposed method uses 3D shape features to generate promising hypotheses within range images and
verifies these hypotheses by using features obtained from both range and color images.
Interactive Full-Body Motion Capture Using Infrared Sensor Network ijcga
Traditional motion capture (mocap) has been well-studied in visual science for the last decades. However the field is mostly about capturing precise animation to be used in specific applications after intensive post processing such as studying biomechanics or rigging models in movies. These data sets are normally captured in complex laboratory environments with sophisticated equipment thus making motion capture a
field that is mostly exclusive to professional animators. In addition, obtrusive sensors must be attached to actors and calibrated within the capturing system, resulting in limited and unnatural motion. In recent year the rise of computer vision and interactive entertainment opened the gate for a different type of motion capture which focuses on producing optical markerless or mechanical sensorless motion capture. Furthermore a wide array of low-cost device are released that are easy to use for less mission critical applications. This paper describes a new technique of using multiple infrared devices to process data from multiple infrared sensors to enhance the flexibility and accuracy of the markerless mocap using commodity
devices such as Kinect. The method involves analyzing each individual sensor data, decompose and rebuild
them into a uniformed skeleton across all sensors. We then assign criteria to define the confidence level of
captured signal from sensor. Each sensor operates on its own process and communicates through MPI.
Our method emphasizes on the need of minimum calculation overhead for better real time performance
while being able to maintain good scalability.
Intelligent indoor mobile robot navigation using stereo visionsipij
Majority of the existing robot navigation systems, which facilitate the use of laser range finders, sonar
sensors or artificial landmarks, has the ability to locate itself in an unknown environment and then build a
map of the corresponding environment. Stereo vision,while still being a rapidly developing technique in the
field of autonomous mobile robots, are currently less preferable due to its high implementation cost. This
paper aims at describing an experimental approach for the building of a stereo vision system that helps the
robots to avoid obstacles and navigate through indoor environments and at the same time remaining very
much cost effective. This paper discusses the fusion techniques of stereo vision and ultrasound sensors
which helps in the successful navigation through different types of complex environments. The data from
the sensor enables the robot to create the two dimensional topological map of unknown environments and
stereo vision systems models the three dimension model of the same environment.
Interactive full body motion capture using infrared sensor networkijcga
Traditional motion capture (mocap) has been
well
-
stud
ied in visual science for
the last decades
. However
the fie
ld is mostly about capturing
precise animation to be used in
specific
application
s
after
intensive
post
processing such as studying biomechanics or rigging models in movies. These data set
s are normally
captured in complex laboratory environments with
sophisticated
equipment thus making motion capture a
field that is mostly exclusive to professional animators.
In
addition
, obtrusive sensors must be attached to
actors and calibrated within t
he capturing system, resulting in limited and unnatural motion.
In recent year
the rise of computer vision and interactive entertainment opened the gate for a different type of motion
capture which focuses on producing
optical
marker
less
or mechanical sens
orless
motion capture.
Furtherm
ore a wide array of low
-
cost
device are released that are easy to use
for less mission critical
applications
.
This paper
describe
s
a new technique of using multiple infrared devices to process data from
multiple infrared sensors to enhance the flexibility and accuracy of the markerless mocap
using commodity
devices such as Kinect
. The method involves analyzing each individual sensor
data, decompose and rebuild
them into a uniformed skeleton across all sensors. We then assign criteria to define the confidence level of
captured signal from
sensor. Each sensor operates on its own process and communicates through MPI.
Our method emphasize
s on the need of minimum calculation overhead for better real time performance
while being able to maintain good scalability
Gesture Recognition Review: A Survey of Various Gesture Recognition AlgorithmsIJRES Journal
This paper presents simple as well as effective methods to realize hand gesture recognition. Gesture recognition is mainly apprehensive on analysing the functionality of human Intelligence. The main aim of gesture detection and recognition is to design an efficient system which is able to recognize particular human gestures and use these detected gestures to transfer information or for controlling devices. Hand gestures enable a vivid complementary modal to communicate with speech for expressing ones thought of idea. The information which is associated with hand gestures detection in a conversation is extent or degree, detection discourse structure, spatial and temporal design structure. Based on the above given points the paper discusses various models of gesture detection and recognition.
Digital 3D imaging can benefit from advances in VLSI technology in order to accelerate its deployment in many fields like visual communication and industrial automation. High-resolution 3D images can be acquired using laser-based vision systems. With this approach, the 3D information becomes relatively insensitive to background illumination and surface texture. Complete images of visible surfaces that are rather featureless to the human eye or a video camera can be generated. Intelligent digitizers will be capable of measuring accurately and simultaneously color and 3D.
This paper presents the maneuver of mouse pointer and performs various mouse operations such as left
click, right click, double click, drag etc using gestures recognition technique. Recognizing gestures is a
complex task which involves many aspects such as motion modeling, motion analysis, pattern recognition
and machine learning.
Keeping all the essential factors in mind a system has been created which recognizes the movement of
fingers and various patterns formed by them. Color caps have been used for fingers to distinguish it from
the background color such as skin color. Thus recognizing the gestures various mouse events have been
performed. The application has been created on MATLAB environment with operating system as windows
7.
Object Detection for Service Robot Using Range and Color Features of an ImageIJCSEA Journal
In real-world applications, service robots need to locate and identify objects in a scene. A range sensor provides a robust estimate of depth information, which is useful to accurately locate objects in a scene. On the other hand, color information is an important property for object recognition task. The objective of this paper is to detect and localize multiple objects within an image using both range and color features. The proposed method uses 3D shape features to generate promising hypotheses within range images and verifies these hypotheses by using features obtained from both range and color images.
Object detection for service robot using range and color features of an imageIJCSEA Journal
In real-world applications, service robots need to locate and identify objects in a scene. A range sensor
provides a robust estimate of depth information, which is useful to accurately locate objects in a scene. On
the other hand, color information is an important property for object recognition task. The objective of this
paper is to detect and localize multiple objects within an image using both range and color features. The
proposed method uses 3D shape features to generate promising hypotheses within range images and
verifies these hypotheses by using features obtained from both range and color images.
Interactive Full-Body Motion Capture Using Infrared Sensor Network ijcga
Traditional motion capture (mocap) has been well-studied in visual science for the last decades. However the field is mostly about capturing precise animation to be used in specific applications after intensive post processing such as studying biomechanics or rigging models in movies. These data sets are normally captured in complex laboratory environments with sophisticated equipment thus making motion capture a
field that is mostly exclusive to professional animators. In addition, obtrusive sensors must be attached to actors and calibrated within the capturing system, resulting in limited and unnatural motion. In recent year the rise of computer vision and interactive entertainment opened the gate for a different type of motion capture which focuses on producing optical markerless or mechanical sensorless motion capture. Furthermore a wide array of low-cost device are released that are easy to use for less mission critical applications. This paper describes a new technique of using multiple infrared devices to process data from multiple infrared sensors to enhance the flexibility and accuracy of the markerless mocap using commodity
devices such as Kinect. The method involves analyzing each individual sensor data, decompose and rebuild
them into a uniformed skeleton across all sensors. We then assign criteria to define the confidence level of
captured signal from sensor. Each sensor operates on its own process and communicates through MPI.
Our method emphasizes on the need of minimum calculation overhead for better real time performance
while being able to maintain good scalability.
Intelligent indoor mobile robot navigation using stereo visionsipij
Majority of the existing robot navigation systems, which facilitate the use of laser range finders, sonar
sensors or artificial landmarks, has the ability to locate itself in an unknown environment and then build a
map of the corresponding environment. Stereo vision,while still being a rapidly developing technique in the
field of autonomous mobile robots, are currently less preferable due to its high implementation cost. This
paper aims at describing an experimental approach for the building of a stereo vision system that helps the
robots to avoid obstacles and navigate through indoor environments and at the same time remaining very
much cost effective. This paper discusses the fusion techniques of stereo vision and ultrasound sensors
which helps in the successful navigation through different types of complex environments. The data from
the sensor enables the robot to create the two dimensional topological map of unknown environments and
stereo vision systems models the three dimension model of the same environment.
Interactive full body motion capture using infrared sensor networkijcga
Traditional motion capture (mocap) has been
well
-
stud
ied in visual science for
the last decades
. However
the fie
ld is mostly about capturing
precise animation to be used in
specific
application
s
after
intensive
post
processing such as studying biomechanics or rigging models in movies. These data set
s are normally
captured in complex laboratory environments with
sophisticated
equipment thus making motion capture a
field that is mostly exclusive to professional animators.
In
addition
, obtrusive sensors must be attached to
actors and calibrated within t
he capturing system, resulting in limited and unnatural motion.
In recent year
the rise of computer vision and interactive entertainment opened the gate for a different type of motion
capture which focuses on producing
optical
marker
less
or mechanical sens
orless
motion capture.
Furtherm
ore a wide array of low
-
cost
device are released that are easy to use
for less mission critical
applications
.
This paper
describe
s
a new technique of using multiple infrared devices to process data from
multiple infrared sensors to enhance the flexibility and accuracy of the markerless mocap
using commodity
devices such as Kinect
. The method involves analyzing each individual sensor
data, decompose and rebuild
them into a uniformed skeleton across all sensors. We then assign criteria to define the confidence level of
captured signal from
sensor. Each sensor operates on its own process and communicates through MPI.
Our method emphasize
s on the need of minimum calculation overhead for better real time performance
while being able to maintain good scalability
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Leader Follower Formation Control of Ground Vehicles Using Dynamic Pixel Coun...ijma
This paper deals with leader-follower formations of non-holonomic mobile robots, introducing a formation
control strategy based on pixel counts using a commercial grade electro optics camera. Localization of the
leader for motions along line of sight as well as the obliquely inclined directions are considered based on
pixel variation of the images by referencing to two arbitrarily designated positions in the image frames.
Based on an established relationship between the displacement of the camera movement along the viewing
direction and the difference in pixel counts between reference points in the images, the range and the angle
estimate between the follower camera and the leader is calculated. The Inverse Perspective Transform is
used to account for non linear relationship between the height of vehicle in a forward facing image and its
distance from the camera. The formulation is validated with experiments.
Tiny-YOLO distance measurement and object detection coordination system for t...IJECEIAES
A humanoid robot called BarelangFC was designed to take part in the Kontes Robot Indonesia (KRI) competition, in the robot coordination division. In this division, each robot is expected to recognize its opponents and to pass the ball towards a team member to establish coordination between the robots. In order to achieve this team coordination, a fast and accurate system is needed to detect and estimate the other robot’s position in real time. Moreover, each robot has to estimate its team members’ locations based on its camera reading, so that the ball can be passed without error. This research proposes a Tiny-YOLO deep learning method to detect the location of a team member robot and presents a real-time coordination system using a ZED camera. To establish the coordinate system, the distance between the robots was estimated using a trigonometric equation to ensure that the robot was able to pass the ball towards another robot. To verify our method, real-time experiments was carried out using an NVDIA Jetson NX Xavier, and the results showed that the robot could estimate the distance correctly before passing the ball toward another robot.
Fuzzy-proportional-integral-derivative-based controller for object tracking i...IJECEIAES
This paper aims at designing and implementing an intelligent controller for the orientation control of a two-wheeled mobile robot. The controller is designed in LabVIEW and based on analyzed image parameters from cameras. The image program calculates the distance and angle from the camera to the object. The fuzzy controller will get these parameters as crisp input data and send the calculated velocity as crisp output data to the right and left wheel motor for the robot tracking the target object. The results show that the controller gives a fast response and high reliability and quickly carries out data recovery from system faults. The system also works well in the uncertainties of process variables and without mathematical modeling.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Enhanced target tracking based on mean shift algorithm for satellite imageryeSAT Journals
Abstract Target tracking in high resolution satellite images is challenging task for computer vision field. In this paper we have proposed a mean shift algorithm based enhanced target tracking system for high resolution satellite imagery. In proposed tracking algorithm, Target modeling is done using spectral features of target object i.e. Mean & Energy density function. Feature Vector space with minimum Euclidean Distance is used for predicting next possible position of target object in consecutive frames. Proposed tracking algorithm has been tested using two high resolution databases i.e. Harbor & Airport region database acquired by WorldView-2 satellite at different times. Recall, Precision & F1 score etc. performance parameters are also calculated for showing the tracking ability of the proposed method in real-time applications and are compared with the results of Regional Operator Design based tracking algorithm proposed in [1]. The results show that our proposed method gives relatively better performance than the other tracking algorithms used in satellite imagery. Keywords- Target tracking, Mean shift algorithm, Energy density function, Feature Vector Space, Frame
REGISTRATION TECHNOLOGIES and THEIR CLASSIFICATION IN AUGMENTED REALITY THE K...IJCSEA Journal
The registration in augmented reality is process which merges virtual objects generated by computer with
real world image caught by camera. This paper describes the knowledge-based registration, computer
vision-based registration and tracker-based registration technology. This paper mainly focused on trackerbased registration technology in augmented reality. Also described method in tracker- based technology,
problem and solution.
REGISTRATION TECHNOLOGIES and THEIR CLASSIFICATION IN AUGMENTED REALITY THE K...IJCSEA Journal
The registration in augmented reality is process which merges virtual objects generated by computer with real world image caught by camera. This paper describes the knowledge-based registration, computer vision-based registration and tracker-based registration technology. This paper mainly focused on trackerbased
registration technology in augmented reality. Also described method in tracker- based technology, problem and solution.
Pose estimation algorithm for mobile augmented reality based on inertial sen...IJECEIAES
Augmented reality (AR) applications have become increasingly ubiquitous as it integrates virtual information such as images, 3D objects, video, and more to the real world, which further enhances the real environment. Many researchers have investigated the augmentation of the 3D object on the digital screen. However, certain loopholes exist in the existing system while estimating the object’s pose, making it inaccurate for mobile augmented reality (MAR) applications. Objects augmented in the current system have much jitter due to frame illumination changes, affecting the accuracy of vision-based pose estimation. This paper proposes to estimate the pose of an object by blending both vision-based techniques and micro electrical mechanical system (MEMS) sensor (gyroscope) to minimize the jitter problem in MAR. The algorithm used for feature detection and description is oriented FAST rotated BRIEF (ORB), whereas to evaluate the homography for pose estimation, random sample consensus (RANSAC) is used. Furthermore, gyroscope sensor data is incorporated with the vision-based pose estimation. We evaluated the performance of augmenting the 3D object using the techniques, vision-based, and incorporating the sensor data using the video data. After extensive experiments, the validity of the proposed method was superior to the existing vision-based pose estimation algorithms.
Automatic 3D view Generation from a Single 2D Image for both Indoor and Outdo...ijcsa
Image based video generation paradigms have recently emerged as an interesting problem in the field of robotics. This paper focuses on the problem of automatic video generation of both indoor and outdoor scenes. Automatic 3D view generation of indoor scenes mainly consist of orthogonal planes and outdoor scenes consist of vanishing point. The algorithm infers frontier information directly from the images using a geometric context-based segmentation scheme that uses the natural scene structure. The presence of floor is a major cue for obtaining the termination point for the video generation of the indoor scenes and vanishing point plays an important role in case of outdoor scenes. In both the cases, we create the navigation by cropping the image to the desired size upto the termination point. Our approach is fully automatic, since it needs no human intervention and finds applications, mainly in assisting autonomous cars, virtual walk through ancient time images, in architectural sites and in forensics. Qualitative and quantitative experiments on nearly 250 images in different scenarios show that the proposed algorithms are more efficient and accurate.
Design and implementation of video tracking system based on camera field of viewsipij
The basic idea of this paper is to design and implement of video tracking system based on Camera Field of
View (CFOV), Otsu’s method was used to detect targets such as vehicles and people. Whereas most
algorithms were spent a lot of time to execute the process, an algorithm was developed to achieve it in a
little time. The histogram projection was used in both directional to detect target from search region,
which is robust to various light conditions in Charge Couple Device (CCD) camera images and saves
computation time.
Our algorithm based on background subtraction, and normalize cross correlation operation from a series
of sequential sub images can estimate the motion vector. Camera field of view (CFOV) was determined and
calibrated to find the relation between real distance and image distance. The system was tested by
measuring the real position of object in the laboratory and compares it with the result of computed one. So
these results are promising to develop the system in future.
A Fast Single-Pixel Laser Imager for VR/AR Headset TrackingPing Hsu
In this work we demonstrate a highly flexible laser imaging system for 3D sensing applications such as in tracking of VR/AR headsets, hands and gestures. The system uses a MEMS mirror scan module to transmit low power laser pulses over programmable areas within a field of view and uses a single photodiode to measure the reflected light...
Similar to Goal location prediction based on deep learning using RGB-D camera (20)
Square transposition: an approach to the transposition process in block cipherjournalBEEI
The transposition process is needed in cryptography to create a diffusion effect on data encryption standard (DES) and advanced encryption standard (AES) algorithms as standard information security algorithms by the National Institute of Standards and Technology. The problem with DES and AES algorithms is that their transposition index values form patterns and do not form random values. This condition will certainly make it easier for a cryptanalyst to look for a relationship between ciphertexts because some processes are predictable. This research designs a transposition algorithm called square transposition. Each process uses square 8 × 8 as a place to insert and retrieve 64-bits. The determination of the pairing of the input scheme and the retrieval scheme that have unequal flow is an important factor in producing a good transposition. The square transposition can generate random and non-pattern indices so that transposition can be done better than DES and AES.
Hyper-parameter optimization of convolutional neural network based on particl...journalBEEI
Deep neural networks have accomplished enormous progress in tackling many problems. More specifically, convolutional neural network (CNN) is a category of deep networks that have been a dominant technique in computer vision tasks. Despite that these deep neural networks are highly effective; the ideal structure is still an issue that needs a lot of investigation. Deep Convolutional Neural Network model is usually designed manually by trials and repeated tests which enormously constrain its application. Many hyper-parameters of the CNN can affect the model performance. These parameters are depth of the network, numbers of convolutional layers, and numbers of kernels with their sizes. Therefore, it may be a huge challenge to design an appropriate CNN model that uses optimized hyper-parameters and reduces the reliance on manual involvement and domain expertise. In this paper, a design architecture method for CNNs is proposed by utilization of particle swarm optimization (PSO) algorithm to learn the optimal CNN hyper-parameters values. In the experiment, we used Modified National Institute of Standards and Technology (MNIST) database of handwritten digit recognition. The experiments showed that our proposed approach can find an architecture that is competitive to the state-of-the-art models with a testing error of 0.87%.
Supervised machine learning based liver disease prediction approach with LASS...journalBEEI
In this contemporary era, the uses of machine learning techniques are increasing rapidly in the field of medical science for detecting various diseases such as liver disease (LD). Around the globe, a large number of people die because of this deadly disease. By diagnosing the disease in a primary stage, early treatment can be helpful to cure the patient. In this research paper, a method is proposed to diagnose the LD using supervised machine learning classification algorithms, namely logistic regression, decision tree, random forest, AdaBoost, KNN, linear discriminant analysis, gradient boosting and support vector machine (SVM). We also deployed a least absolute shrinkage and selection operator (LASSO) feature selection technique on our taken dataset to suggest the most highly correlated attributes of LD. The predictions with 10 fold cross-validation (CV) made by the algorithms are tested in terms of accuracy, sensitivity, precision and f1-score values to forecast the disease. It is observed that the decision tree algorithm has the best performance score where accuracy, precision, sensitivity and f1-score values are 94.295%, 92%, 99% and 96% respectively with the inclusion of LASSO. Furthermore, a comparison with recent studies is shown to prove the significance of the proposed system.
A secure and energy saving protocol for wireless sensor networksjournalBEEI
The research domain for wireless sensor networks (WSN) has been extensively conducted due to innovative technologies and research directions that have come up addressing the usability of WSN under various schemes. This domain permits dependable tracking of a diversity of environments for both military and civil applications. The key management mechanism is a primary protocol for keeping the privacy and confidentiality of the data transmitted among different sensor nodes in WSNs. Since node's size is small; they are intrinsically limited by inadequate resources such as battery life-time and memory capacity. The proposed secure and energy saving protocol (SESP) for wireless sensor networks) has a significant impact on the overall network life-time and energy dissipation. To encrypt sent messsages, the SESP uses the public-key cryptography’s concept. It depends on sensor nodes' identities (IDs) to prevent the messages repeated; making security goals- authentication, confidentiality, integrity, availability, and freshness to be achieved. Finally, simulation results show that the proposed approach produced better energy consumption and network life-time compared to LEACH protocol; sensors are dead after 900 rounds in the proposed SESP protocol. While, in the low-energy adaptive clustering hierarchy (LEACH) scheme, the sensors are dead after 750 rounds.
Plant leaf identification system using convolutional neural networkjournalBEEI
This paper proposes a leaf identification system using convolutional neural network (CNN). This proposed system can identify five types of local Malaysia leaf which were acacia, papaya, cherry, mango and rambutan. By using CNN from deep learning, the network is trained from the database that acquired from leaf images captured by mobile phone for image classification. ResNet-50 was the architecture has been used for neural networks image classification and training the network for leaf identification. The recognition of photographs leaves requested several numbers of steps, starting with image pre-processing, feature extraction, plant identification, matching and testing, and finally extracting the results achieved in MATLAB. Testing sets of the system consists of 3 types of images which were white background, and noise added and random background images. Finally, interfaces for the leaf identification system have developed as the end software product using MATLAB app designer. As a result, the accuracy achieved for each training sets on five leaf classes are recorded above 98%, thus recognition process was successfully implemented.
Customized moodle-based learning management system for socially disadvantaged...journalBEEI
This study aims to develop Moodle-based LMS with customized learning content and modified user interface to facilitate pedagogical processes during covid-19 pandemic and investigate how teachers of socially disadvantaged schools perceived usability and technology acceptance. Co-design process was conducted with two activities: 1) need assessment phase using an online survey and interview session with the teachers and 2) the development phase of the LMS. The system was evaluated by 30 teachers from socially disadvantaged schools for relevance to their distance learning activities. We employed computer software usability questionnaire (CSUQ) to measure perceived usability and the technology acceptance model (TAM) with insertion of 3 original variables (i.e., perceived usefulness, perceived ease of use, and intention to use) and 5 external variables (i.e., attitude toward the system, perceived interaction, self-efficacy, user interface design, and course design). The average CSUQ rating exceeded 5.0 of 7 point-scale, indicated that teachers agreed that the information quality, interaction quality, and user interface quality were clear and easy to understand. TAM results concluded that the LMS design was judged to be usable, interactive, and well-developed. Teachers reported an effective user interface that allows effective teaching operations and lead to the system adoption in immediate time.
Understanding the role of individual learner in adaptive and personalized e-l...journalBEEI
Dynamic learning environment has emerged as a powerful platform in a modern e-learning system. The learning situation that constantly changing has forced the learning platform to adapt and personalize its learning resources for students. Evidence suggested that adaptation and personalization of e-learning systems (APLS) can be achieved by utilizing learner modeling, domain modeling, and instructional modeling. In the literature of APLS, questions have been raised about the role of individual characteristics that are relevant for adaptation. With several options, a new problem has been raised where the attributes of students in APLS often overlap and are not related between studies. Therefore, this study proposed a list of learner model attributes in dynamic learning to support adaptation and personalization. The study was conducted by exploring concepts from the literature selected based on the best criteria. Then, we described the results of important concepts in student modeling and provided definitions and examples of data values that researchers have used. Besides, we also discussed the implementation of the selected learner model in providing adaptation in dynamic learning.
Prototype mobile contactless transaction system in traditional markets to sup...journalBEEI
One way to prevent and reduce the spread of the covid-19 pandemic is through physical distancing program. This research aims to develop a prototype contactless transaction system using digital payment mechanisms and QR code technology that will be applied in traditional markets. The method used in the development of electronic market systems is a prototype approach. The application of QR code and digital payments are used as a solution to minimize money exchange contacts that are common in traditional markets. The results showed that the system built was able to accelerate and facilitate the buying and selling transaction process in traditional market environment. Alpha testing shows that all functional systems are running well. Meanwhile, beta testing shows that the user can very well accept the system that was built. The results of the study also show acceptance of the usefulness of the system being built, as well as the optimism of its users to be able to take advantage of this system both technologically and functionally, so its can be a part of the digital transformation of the traditional market to the electronic market and has become one of the solutions in reducing the spread of the current covid-19 pandemic.
Wireless HART stack using multiprocessor technique with laxity algorithmjournalBEEI
The use of a real-time operating system is required for the demarcation of industrial wireless sensor network (IWSN) stacks (RTOS). In the industrial world, a vast number of sensors are utilised to gather various types of data. The data gathered by the sensors cannot be prioritised ahead of time. Because all of the information is equally essential. As a result, a protocol stack is employed to guarantee that data is acquired and processed fairly. In IWSN, the protocol stack is implemented using RTOS. The data collected from IWSN sensor nodes is processed using non-preemptive scheduling and the protocol stack, and then sent in parallel to the IWSN's central controller. The real-time operating system (RTOS) is a process that occurs between hardware and software. Packets must be sent at a certain time. It's possible that some packets may collide during transmission. We're going to undertake this project to get around this collision. As a prototype, this project is divided into two parts. The first uses RTOS and the LPC2148 as a master node, while the second serves as a standard data collection node to which sensors are attached. Any controller may be used in the second part, depending on the situation. Wireless HART allows two nodes to communicate with each other.
Implementation of double-layer loaded on octagon microstrip yagi antennajournalBEEI
A double-layer loaded on the octagon microstrip yagi antenna (OMYA) at 5.8 GHz industrial, scientific and medical (ISM) Band is investigated in this paper. The double-layer consist of two double positive (DPS) substrates. The OMYA is overlaid with a double-layer configuration were simulated, fabricated and measured. A good agreement was observed between the computed and measured results of the gain for this antenna. According to comparison results, it shows that 2.5 dB improvement of the OMYA gain can be obtained by applying the double-layer on the top of the OMYA. Meanwhile, the bandwidth of the measured OMYA with the double-layer is 14.6%. It indicates that the double-layer can be used to increase the OMYA performance in term of gain and bandwidth.
The calculation of the field of an antenna located near the human headjournalBEEI
In this work, a numerical calculation was carried out in one of the universal programs for automatic electro-dynamic design. The calculation is aimed at obtaining numerical values for specific absorbed power (SAR). It is the SAR value that can be used to determine the effect of the antenna of a wireless device on biological objects; the dipole parameters will be selected for GSM1800. Investigation of the influence of distance to a cell phone on radiation shows that absorbed in the head of a person the effect of electromagnetic radiation on the brain decreases by three times this is a very important result the SAR value has decreased by almost three times it is acceptable results.
Exact secure outage probability performance of uplinkdownlink multiple access...journalBEEI
In this paper, we study uplink-downlink non-orthogonal multiple access (NOMA) systems by considering the secure performance at the physical layer. In the considered system model, the base station acts a relay to allow two users at the left side communicate with two users at the right side. By considering imperfect channel state information (CSI), the secure performance need be studied since an eavesdropper wants to overhear signals processed at the downlink. To provide secure performance metric, we derive exact expressions of secrecy outage probability (SOP) and and evaluating the impacts of main parameters on SOP metric. The important finding is that we can achieve the higher secrecy performance at high signal to noise ratio (SNR). Moreover, the numerical results demonstrate that the SOP tends to a constant at high SNR. Finally, our results show that the power allocation factors, target rates are main factors affecting to the secrecy performance of considered uplink-downlink NOMA systems.
Design of a dual-band antenna for energy harvesting applicationjournalBEEI
This report presents an investigation on how to improve the current dual-band antenna to enhance the better result of the antenna parameters for energy harvesting application. Besides that, to develop a new design and validate the antenna frequencies that will operate at 2.4 GHz and 5.4 GHz. At 5.4 GHz, more data can be transmitted compare to 2.4 GHz. However, 2.4 GHz has long distance of radiation, so it can be used when far away from the antenna module compare to 5 GHz that has short distance in radiation. The development of this project includes the scope of designing and testing of antenna using computer simulation technology (CST) 2018 software and vector network analyzer (VNA) equipment. In the process of designing, fundamental parameters of antenna are being measured and validated, in purpose to identify the better antenna performance.
Transforming data-centric eXtensible markup language into relational database...journalBEEI
eXtensible markup language (XML) appeared internationally as the format for data representation over the web. Yet, most organizations are still utilising relational databases as their database solutions. As such, it is crucial to provide seamless integration via effective transformation between these database infrastructures. In this paper, we propose XML-REG to bridge these two technologies based on node-based and path-based approaches. The node-based approach is good to annotate each positional node uniquely, while the path-based approach provides summarised path information to join the nodes. On top of that, a new range labelling is also proposed to annotate nodes uniquely by ensuring the structural relationships are maintained between nodes. If a new node is to be added to the document, re-labelling is not required as the new label will be assigned to the node via the new proposed labelling scheme. Experimental evaluations indicated that the performance of XML-REG exceeded XMap, XRecursive, XAncestor and Mini-XML concerning storing time, query retrieval time and scalability. This research produces a core framework for XML to relational databases (RDB) mapping, which could be adopted in various industries.
Key performance requirement of future next wireless networks (6G)journalBEEI
Given the massive potentials of 5G communication networks and their foreseeable evolution, what should there be in 6G that is not in 5G or its long-term evolution? 6G communication networks are estimated to integrate the terrestrial, aerial, and maritime communications into a forceful network which would be faster, more reliable, and can support a massive number of devices with ultra-low latency requirements. This article presents a complete overview of potential 6G communication networks. The major contribution of this study is to present a broad overview of key performance indicators (KPIs) of 6G networks that cover the latest manufacturing progress in the environment of the principal areas of research application, and challenges.
Noise resistance territorial intensity-based optical flow using inverse confi...journalBEEI
This paper presents the use of the inverse confidential technique on bilateral function with the territorial intensity-based optical flow to prove the effectiveness in noise resistance environment. In general, the image’s motion vector is coded by the technique called optical flow where the sequences of the image are used to determine the motion vector. But, the accuracy rate of the motion vector is reduced when the source of image sequences is interfered by noises. This work proved that the inverse confidential technique on bilateral function can increase the percentage of accuracy in the motion vector determination by the territorial intensity-based optical flow under the noisy environment. We performed the testing with several kinds of non-Gaussian noises at several patterns of standard image sequences by analyzing the result of the motion vector in a form of the error vector magnitude (EVM) and compared it with several noise resistance techniques in territorial intensity-based optical flow method.
Modeling climate phenomenon with software grids analysis and display system i...journalBEEI
This study aims to model climate change based on rainfall, air temperature, pressure, humidity and wind with grADS software and create a global warming module. This research uses 3D model, define, design, and develop. The results of the modeling of the five climate elements consist of the annual average temperature in Indonesia in 2009-2015 which is between 29oC to 30.1oC, the horizontal distribution of the annual average pressure in Indonesia in 2009-2018 is between 800 mBar to 1000 mBar, the horizontal distribution the average annual humidity in Indonesia in 2009 and 2011 ranged between 27-57, in 2012-2015, 2017 and 2018 it ranged between 30-60, during the East Monsoon, the wind circulation moved from northern Indonesia to the southern region Indonesia. During the west monsoon, the wind circulation moves from the southern part of Indonesia to the northern part of Indonesia. The global warming module for SMA/MA produced is feasible to use, this is in accordance with the value given by the validate of 69 which is in the appropriate category and the response of teachers and students through a 91% questionnaire.
An approach of re-organizing input dataset to enhance the quality of emotion ...journalBEEI
The purpose of this paper is to propose an approach of re-organizing input data to recognize emotion based on short signal segments and increase the quality of emotional recognition using physiological signals. MIT's long physiological signal set was divided into two new datasets, with shorter and overlapped segments. Three different classification methods (support vector machine, random forest, and multilayer perceptron) were implemented to identify eight emotional states based on statistical features of each segment in these two datasets. By re-organizing the input dataset, the quality of recognition results was enhanced. The random forest shows the best classification result among three implemented classification methods, with an accuracy of 97.72% for eight emotional states, on the overlapped dataset. This approach shows that, by re-organizing the input dataset, the high accuracy of recognition results can be achieved without the use of EEG and ECG signals.
Parking detection system using background subtraction and HSV color segmentationjournalBEEI
Manual system vehicle parking makes finding vacant parking lots difficult, so it has to check directly to the vacant space. If many people do parking, then the time needed for it is very much or requires many people to handle it. This research develops a real-time parking system to detect parking. The system is designed using the HSV color segmentation method in determining the background image. In addition, the detection process uses the background subtraction method. Applying these two methods requires image preprocessing using several methods such as grayscaling, blurring (low-pass filter). In addition, it is followed by a thresholding and filtering process to get the best image in the detection process. In the process, there is a determination of the ROI to determine the focus area of the object identified as empty parking. The parking detection process produces the best average accuracy of 95.76%. The minimum threshold value of 255 pixels is 0.4. This value is the best value from 33 test data in several criteria, such as the time of capture, composition and color of the vehicle, the shape of the shadow of the object’s environment, and the intensity of light. This parking detection system can be implemented in real-time to determine the position of an empty place.
Quality of service performances of video and voice transmission in universal ...journalBEEI
The universal mobile telecommunications system (UMTS) has distinct benefits in that it supports a wide range of quality of service (QoS) criteria that users require in order to fulfill their requirements. The transmission of video and audio in real-time applications places a high demand on the cellular network, therefore QoS is a major problem in these applications. The ability to provide QoS in the UMTS backbone network necessitates an active QoS mechanism in order to maintain the necessary level of convenience on UMTS networks. For UMTS networks, investigation models for end-to-end QoS, total transmitted and received data, packet loss, and throughput providing techniques are run and assessed and the simulation results are examined. According to the results, appropriate QoS adaption allows for specific voice and video transmission. Finally, by analyzing existing QoS parameters, the QoS performance of 4G/UMTS networks may be improved.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
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Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdf
Goal location prediction based on deep learning using RGB-D camera
1. Bulletin of Electrical Engineering and Informatics
Vol. 10, No. 5, October 2021, pp. 2811~2820
ISSN: 2302-9285, DOI: 10.11591/eei.v10i5.3170 2811
Journal homepage: http://beei.org
Goal location prediction based on deep learning using RGB-D
camera
Heba Hakim1
, Zaineb Alhakeem2
, Salah Al-Darraji3
1
Department of Computers Engineering, Basrah University, Iraq
2
Department of Communication Engineering, Iraq University College, Iraq
3
Department of Computer Sciences, Basrah University, Iraq
Article Info ABSTRACT
Article history:
Received May 26, 2021
Revised Jul 30, 2021
Accepted Aug 31, 2021
In the navigation system, the desired destination position plays an essential
role since the path planning algorithms takes a current location and goal
location as inputs as well as the map of the surrounding environment. The
generated path from path planning algorithm is used to guide a user to his
final destination. This paper presents a proposed algorithm based on RGB-D
camera to predict the goal coordinates in 2D occupancy grid map for visually
impaired people navigation system. In recent years, deep learning methods
have been used in many object detection tasks. So, the object detection
method based on convolution neural network method is adopted in the
proposed algorithm. The measuring distance between the current position of a
sensor and the detected object depends on the depth data that is acquired from
RGB-D camera. Both of the object detected coordinates and depth data has
been integrated to get an accurate goal location in a 2D map. This proposed
algorithm has been tested on various real-time scenarios. The experiments
results indicate to the effectiveness of the proposed algorithm.
Keywords:
Computer vision
Deeep learning
Depth sensor
Object detection
Object recognition
This is an open access article under the CC BY-SA license.
Corresponding Author:
Heba Hakim
Department of Computers Engineering
Basrah University, Iraq-Basrah
Email: hebah.hakem@gmail.com
1. INTRODUCTION
Person with healthy vision determines his orientation in the surrounding environment, moves from
one place to another and distinguishes things and places without any difficult. Unfortunately, visually
impaired person (VI) encounters many problems in his daily life. Therefore, numerous navigation assistive
devices have been implemented to aim VI person and increase his self-confidence. [1]-[5]. The navigation
system means the ability to find a current location, generating the optimal path to the desired destination. In
order to achieve a full autonomous navigation system, full information must be provided such as current
location, destination location and a map of the surrounding environment. Some navigation systems use
simultaneous localization and mapping (SLAM) [6]-[9] approaches to construct 2D or 3D map of their
surroundings. These approaches concern with constructing a map of unknown environment depending on the
acquired data from the sensor and simultaneously compute the mobility system's position within a map.
Some of SLAM algorithms depend on LiDAR (light detection and ranging) [10]-[12] while others based on
RGB-D camera [13]-[15]. Since the coordinates of the goal in navigation system is needed, the object
detection method with data of a RGB-D camera has been used in this work to achieve that. In recent years,
convolution neural networks have been applied with major breakthrough success to recognition, detection,
and segmentation of objects in images. Object detection is one of an important task in computer vision that
2. ISSN: 2302-9285
Bulletin of Electr Eng & Inf, Vol. 10, No. 5, October 2021 : 2811 – 2820
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deals with recognizing objects of a certain class (i.e. car, animal, human) and localizing them in digital
image. Now, object detection has widely been used in various real-time applications (i.e. robot vision,
autonomous driving). There are many methods of object detection that uses convolution neural networks
(CNNs) [16], [17] such as R-CNN [18], fast R-CNN [19], faster R-CNN [20], single shot multibox detector
(SSD) [21], you only look once (YOLO) [22]. Figure 1 and Figure 2 provide the comparison on the common
object detection methods accuracy and speed, respectively. As shown from these figures, YOLO v2 [23]
approach provides a good tradeoff between the precision and speed. So, this approach has been used in our
proposed algorithm.
Figure 1. The accuracy of common object detection method on pascal VOC dataset
Figure 2. The speed of common object detection method on pascal VOC dataset
2. THE PROPOSED SYSTEM
Any navigation system required a 2D map, current location of user and final destination to generate
a path that will be followed. Both of the current position of user and 2D map of unknown surrounding
environment are not a focus of this paper, as there are many SLAM methods available for that. Therefore, to
specify the coordinate of a desired goal that was selected by VI person, a proposed algorithm that combines
both the results of object detection method based on deep-learning and depth information from RGB-D
camera is implemented in this work.
The proposed algorithm depends on RGB-D camera mounted on a head as shown in Figure 3 that
provides color image and depth data for each pixel in an image. The color image will be used as input to the
object detection method (YOLO v2) in order to predict the class of the detected object and the location of the
recognized object (i.e. bounding box that gives an object class coordinates) in an image. However, the depth
information is used to obtain the distance between the recognized object and user. Both the depth information
and coordinates of the recognized object in an image are integrated in order to obtain the location of an object
(that is considered as a goal) in a 2D map that is used in the navigation system.
3. Bulletin of Electr Eng & Inf ISSN: 2302-9285
Goal location prediction based on deep learning using RGB-D camera (Heba Hakim)
2813
Figure 3. Assistive wearable device using RGB-D camera
The block diagram of proposed algorithm in Figure 4 starts with applying object detection method
to recognize the object class. After that, the type of the recognized object is converted to voice command by
text-to-speech (TTS) process (ESpeak TTS method) to notify visually impaired person with information of
his surroundings. The visually impaired person selects his desired goal among the recognized objects on the
voice command through the building microphone of the RGB-D camera. The speech recognition module is
used to convert the VI person's voice to text in order to match the selected destination with any of the
recognized object types. The coordinates of bounding box for the selected destination and its depth are taken
to obtain a goal coordinate to the navigation system.
Figure 4. The block diagram of the proposed algorithm
2.1. RGB-D camera
Asus Xtion sensor is one of the most popular active 3D-camera which is introduced in 2012 by a
company of PrimeSense in collaboration with Asus company. The first generation is Asus Xtion Pro that
only provides a depth camera. After that, the Xtion Pro Live version has been released which provides RGB
camera and depth ..data. It is a structured light camera where the principle of triangulation is used to measure
the depth for each pixel. Asus Xtion Pro Live comprised of a VGA camera to capture RGB image, depth
sensor measures object distance to the camera to provide a depth image, and 2 microphones. The
specification of Asus Xtion Pro Live listed in Table 1.
Table 1. Asus Xtion Pro Live camera specification
Specifications
RGB image/depth map Resolution 640 480 pixels
Vertical viewing angle 45°
Horizontal viewing angle 58°
Accurate distance range 0.8m – 3.5m
size 170 gm
weight 18×3.5×5 cm
cost ~ 150$
4. ISSN: 2302-9285
Bulletin of Electr Eng & Inf, Vol. 10, No. 5, October 2021 : 2811 – 2820
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With this sensor, it is possible to acquire the color image with 3 channels (red, green, and blue),
each channel is represented by 8 bits, and also depth information in 11 bits for each pixel in RGB-image. The
depth data is expressed in millimeters where the value zero represents that there is no depth information at
that corresponding pixel. The raw depth map is determined by an IR laser source and an IR camera (CMOS
sensor). The IR laser source emits the IR light in the form of a known dot pattern (speckles pattern) by the
diffraction grating on the scene in front of the camera and IR camera reads these reflected spackles. After
that, the depth sensor processor receives the speckle pattern and computes the depth value by correlating the
captured pattern with a stored reference pattern which is located on the plane with a known depth to the
sensor. The depth map is the output of the depth sensor processor. To express the object points 3D
coordinates, the coordinate system of a depth with its origin is considered at the perspective center of the IR
camera as shown in Figure 5.
Figure 5. The schematic representation for relation of depth disparity
The Z-axis is perpendicular to an image plane in the direction of the object, the X-axis is orthogonal
to Z-axis towards the baseline b which represents the distance between the laser projector and IR camera
center, and Y-axis is perpendicular to Z and X making a right-handed coordinate system. Assume that the
point o of an object is on the reference plane at a depth Zr to the camera and a speckle on an object is
captured on the IR camera image plane. The speckle location on the image plane is shifted in the direction of
X once the object is displaced far away from/close to the sensor. This shift is measured as disparity (pixel
offset) d in the image space. From the triangles similarity, the following can be calculated [24], [25]:
𝐷
𝑏
=
𝑍𝑟−𝑍𝑜
𝑍𝑟
(1)
𝐷
𝑑
=
𝑍𝑜
𝑓
(2)
where Zo represents the depth (distance) of a point o in an object space, f is focal length of IR camera, and D
denotes the point o displacement in object space. Zo is expressed in (3) by substituting D from (1) into (2):
𝑍𝑜 =
𝑍𝑟
1+
𝑍𝑟
𝑓𝑏
𝑑𝑓
(3)
The Asus Xtion Pro live sensor in our system works mostly for indoor environment, as the depth
measurement influenced by the direct sunlight. In fact, this camera is not totally unused in outdoor
environments, but it can be used for a cloudy day or a night scene. Asus Xtion Pro Live is with light weight
and small size that allows it suitable to be mounted. Also, the USB 2.0 port of Raspberry pi board powers the
camera by 5v. It transmits RGB-image and depth data per pixel to the system by using the open source
library OpenNI2. OpenNI2 driver is used for sensor interfacing by providing wrappers to many languages
including python. To visualize the RGB and depth image, OpenCV is used by opening ' frame-data'. The 2
microphones of Asus Xtion Pro live distributed on the both sides of the sensor. Each microphone operates in
audio stream of 16-bit with a 16 kHz sampling rate. In this work, the camera's microphone is used to select a
final goal among recognized objects by VI person.
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2.2. You only look once v2 (YOLO v2)
YOLO v2 is an improved approach to YOLO v1 in which the advantage on speed is kept and the
mAP (mean average precision) value of YOLO v1 (63.4%) is increased. In general, YOLO uses single
convolution neural network to predict more than one box and probabilities of class for these boxes. It splits
an image into grid cells of S×S. Each grid is responsible of detecting an object if the object center falls into
this grid cell.
The output tensor of YOLO v2 is with size S×S×(B(5+C)), since each bounding box (BB) predicts:
(1) confidence score which is used to weight this bounding box; (2) the center of bounding box (x,y) relative
to the grid cell and dimension of bounding box (h,w); (3) C class probabilities. YOLO v2 is developed in
order to improve the accuracy by adding Batch normalized in the convolution layer. Besides, it trains the
classifier with images of 224×224 then fine tune the classifier with images of 448 × 448 using much fewer
epochs instead of YOLO training that trains the classifier with images of 224 × 224 then the resolution is
increased to 448 for detection. Also, the idea of anchor box is used to get the best shapes of anchor box that
will be used in predicting. Moreover, the input image was shrunk to 416×416 to get odd number of locations
in the map of feature (i.e. a single center grid cell).
In this work, object detection method depends on YOLO v2; (1) to allow VI person to classify and
distinguish the objects appearing in his path; (2) to provide the location of the classified object that is
represented as a final goal to the navigation system. Tiny YOLO v2 with weight that is pre-trained on
PascalVOC dataset has been specifically adopted in our work. This method is the smallest version of the
complicated YOLO v2. It is lite and faster than original algorithm since it consists of fewer layers that makes
it suitable to apply on Raspberry Pi. Figure 6 shows Tiny YOLO v2 architecture that consists of 9
convolution layers with 6 pooling layers.
Figure 6. Tiny YOLO v2 archeitecture
2.3. The algorithm steps
This subsection illustrated the proposed algorithm of finding goal coordinates on 2D grid map
(represents the 2D occupancy map of the surrounding environment). The proposed algorithm starts with
acquiring the RGB-image in a front of the VI person and its depth raw data from RGB-D camera (Asus Xtion
Pro Live). Firstly, the captured image is resized to (416×416) pixels since the Tiny YOLO v2 uses an image
with this size as input. The value of threshold is set to 0.4 to determine if the detected object is true or not and
pre-trained weight on Pascal VOC data set is loaded. After that, Tiny YOLO v2 is applied to detect the object
category among 20 categories of the dataset (Pascal VOC) and make the bounding box around the object.
The two outputs of the detection process as shown in Figure 7 are:
a. The category of the recognized object, which is converted to voice message by ESpeak TTS method to
notify VI person with the enviroment information to select one of the recognized objects as a goal;
b. Set of coordinates for bounding box (BB) (x-top left, y-top left, x-bottom right, and y-bottom right).
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Figure 7. The process of YOLO v2 on an image
After this process, VI person tells the system where he wants to go (i.e. desired goal) via voice
through the built-in microphone of a depth camera. The voice of VI person is converted by Google speech-
recognition method to text to match the desired goal with one of the detected object classes. The y-top left
coordinate of BB for the selected goal is taken to be used to know the direction of the object with respect to
VI stand (i.e. object lies on the right or left of VI person). This is done by dividing RGB-image into two
equal regions (right region and left region) as shown in Figure 8 and examined y-top left value where it lies.
If this value is between 1 and 208, then the selected object lies on the left of VI person's current position. As
opposite, when this value lies between 209 and 416 that mean the selected object is detected on the right of
VI person standing. While, the minimum depth from depth raw data of this bounding box is used to know the
distance between the VI person and the selected object. Since, the measured depth value is in millimeter
(mm), the following is applied in order to convert it to pixel value on a 2D map:
𝐷𝑒𝑝𝑡ℎ (𝑖𝑛 𝑝𝑖𝑥𝑒𝑙) =
𝐷𝑒𝑝𝑡ℎ 𝑖𝑛 𝑚∗1000
2𝐷 𝑚𝑎𝑝 𝑟𝑒𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛
+ 𝑜𝑟𝑖𝑔𝑖𝑜𝑛 (4)
Where, 2D map resolution represents a grid cell length in (m/pixel).
Each grid cell has a probability of being occupied: (a) black color refers to an occupied cell; (b)
white color refers to a free cell; (c) dark grey color cell refers to area that was not scanned. An obstacle
(occupied cell) in a 2D map is with value 1 while a free cell with value 0.
Thus, all required information to know the coordinate of a selected goal have been available. The
minimum depth value (in pixel) of bounding box for the selected object indicates to x-coordinate of the
selected goal on 2D map. To know the y-coordinate of the selected goal on grid map, all pixels values of the
row with the goal x-coordinate in the right or left of VI person' current position are examined as shown in
Figure 9. It should be noted that the right area or left area relative to the current position of VI person is
specified based on a previous defined area as described in Figure 8. The flowchart of the proposed algorithm
has been described in details in Figure 10 that used the data from RGB-D sensor as input and outputs the
desired goal coordinates on 2D occupancy grid map in real time.
Figure 8. The spliting RGB-image into two areas Figure 9. 2D grid map representation
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Figure 10. The proposed algorithm flowchart
Convert the label of object
class to speech using TTS
Select a desired goal among
the recognizes objects
through mic
𝑐𝑢𝑟𝑟𝑒𝑛𝑡_𝑝𝑜𝑠𝑒(𝑖𝑛 𝑝𝑖𝑥𝑒𝑙)
=
𝑐𝑢𝑟𝑟𝑒𝑛𝑡_𝑝𝑜𝑠𝑒 (𝑖𝑛 𝑚)
𝑚𝑎𝑝_𝑟𝑒𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛
+ 𝑜𝑟𝑔𝑖𝑜𝑛
Input 2D-map & current position
of VI person
Get y-top left coordinate of
BB for a selected goal
𝑥𝑝(𝑖𝑛 𝑝𝑖𝑥𝑒𝑙) =
𝑥 (𝑖𝑛 𝑚𝑚) ∗ 1000
𝑚𝑎𝑝_𝑟𝑒𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛
+ 𝑜𝑟𝑔𝑖𝑜𝑛
Match the selected goal
with a label of recognized
object
Acquire data from sensors
Depth image acquisition Capture RGB image
start
Apply Tiny YOLO v2
Get class of recognized
object
No
Get coordinates of
Bounding Box(BB)
Is this value > (
416
2
)?
Let 𝑥(𝑖𝑛 𝑚𝑚) = min depth of BB for a
selected goal
Search in 2D-map row with no. .𝑥𝑝 from
pixel(𝑥𝑝, 𝑐𝑢𝑟𝑟𝑒𝑛𝑡_𝑝𝑜𝑠𝑒) to
pixel(𝑥𝑝, 416)
Search in 2D-map row with no..𝑥𝑝
from pixel(𝑥𝑝, 1)to
pixel(𝑥𝑝, 𝑐𝑢𝑟𝑟𝑒𝑛𝑡_𝑝𝑜𝑠𝑒)
Let 𝑦𝑝 = y-coordinate for the
first pixel with value (1)
Let 𝑦𝑝 = y-coordinate for the
last pixel with value(1)
Let 𝑔𝑜𝑎𝑙 𝑐𝑜𝑜𝑟𝑑𝑖𝑛𝑎𝑡𝑒𝑠 = (𝑥𝑝, 𝑦𝑝)
End
Convert voice to text using
speech recognition
Output the types of objects
via earphone
Yes
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3. THE EXPERIMENTS AND RESULTS
The proposed algorithm of finding goal coordinates on 2D-map has been evaluated in different real-
time scenarios in the indoor environments. It implemented on Raspberry pi 3 B+ with python-programming
language using Tensorflow1.4, OpenCV2, and OpenNI2 library by using RGB-D camera mounted on the
head. The proposed algorithm is based on the depth sensor that used IR camera. Therefore, the light intensity
of an environment may affect its performance. The measurement errors were plotted in Figure 11 shows the
capability of RGB-D camera to work under which condition in an indoor environment. The RGB-D camera
was placed in different distances away from the object under different light condition. With OpenNI2 library,
it becomes easy to access to a depth value of each pixel as an array. These depth information were written to a
csv file by python language in order to overview and evaluate the depth map obtained by depth sensor.
In Figure 11, the x-axis indicates to the actual distance from the sensor to the obstacle in (m) and y-
axis referred to the maximum deviation value in (m). The deviation was recorded every 0.5 m. As seen from
the overall measurements results, the deviation between the actual depth and calculated depth is very small.
This makes Asus Xtion Pro live a quite useful for our work due to the astonishing precision comparing with
its low cost.
Figure 11. Lighting influence on depth data
In the real-time scenarios in Figures 12 and 13, the coordinates of a desired goal on 2D occupancy
grid map has been determined after a VI person selects the chair as a desired goal. This goal coordinates will
be used in the navigation system to guide VI person from his current position to the desired goal. A red node
in Figure 12-b and 13-b represents the current position of VI person and a blue arrow pointed to a goal
position. These nodes will be taken as start point and end point in path planning module of the navigation system.
(a) (b)
Figure 12. First scenario; (a) real image on 2D map, (b) goal position on 2D map
Deviation
in
(m)
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(a) (b)
Figure 13. Second scenario; (a) real image on 2D map, (b) goal position on 2D map
4. CONCLUSION
This paper presents a proposed algorithm of finding goal coordinates on a 2D occupancy map. This
proposed algorithm has been implemented in order to use it in the indoor navigation system used to help
visually impaired people reach to the desired destination within unknown indoor environments. The proposed
algorithm depends on deep-learning based object detection method using RGB-D camera, which runs on a
lightweight and low-cost main processing platform. Also, the used sensor has the characteristics of small
size, lightweight, and low cost. Thus, it has great potential to be used in a wearable navigation system for a
visually impaired person. The results of experimental verified that the proposed algorithm was effective on
specifying a desired destination coordinates on a 2D map in a real time.
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