The document describes a fast video search algorithm that uses Histogram of Oriented Gradients (HOG) features. HOG features are extracted from frames to create feature vectors. These feature vectors are then quantized and histograms are generated for query and database videos. The algorithm uses an active search approach where histogram similarity is calculated and videos are skipped if dissimilar, improving search speed. The algorithm was tested on a 6 hour video database and achieved a search time of 70ms, over 6 times faster than a conventional approach, and was more robust to noise.
An unsupervised method for real time video shot segmentationcsandit
Segmentation of a video into its constituent shots is a fundamental task for indexing and
analysis in content based video retrieval systems. In this paper, a novel approach is presented
for accurately detecting the shot boundaries in real time video streams, without any a priori
knowledge about the content or type of the video. The edges of objects in a video frame are
detected using a spatio-temporal fuzzy hostility index. These edges are treated as features of the
frame. The correlation between the features is computed for successive incoming frames of the
video. The mean and standard deviation of the correlation values obtained are updated as new
video frames are streamed in. This is done to dynamically set the threshold value using the
three-sigma rule for detecting the shot boundary (abrupt transition). A look back mechanism
forms an important part of the proposed algorithm to detect any missed hard cuts, especially
during the start of the video. The proposed method is shown to be applicable for online video
analysis and summarization systems. In an experimental evaluation on a heterogeneous test set,
consisting of videos from sports, movie songs and music albums, the proposed method achieves
99.24% recall and 99.35% precision on the average.
A New Cross Diamond Search Motion Estimation Algorithm for HEVCIJERA Editor
In this project, a novel approach for motion estimation is proposed. There are few block matching algorithm existing for motion estimation. In motion estimation a new cross diamond search algorithm is implemented compared to diamond search it uses less search point. Because of this we can reduce the computational complexity. The performance of the algorithm is compared with other algorithm by means of search points. This algorithm achieves close performance than that of three step search and diamond search. Compared to all the algorithm cross diamond uses less logic elements, delay and power dissipation.
Reversible Data Hiding in the Spatial and Frequency DomainsCSCJournals
Combinational lossless data hiding in the spatial and frequency domains is proposed. In the spatial domain, a secret message is embedded in a host medium using the min-max algorithm to generate a stego-image. Subsequently, the stego-image is decomposed into the frequency domain via the integer wavelet transform (IWT). Then, a watermark is hidden in the low-high (LH) and high-low (HL) subbands of the IWT domain using the coefficient-bias approach. Simulations show that the perceptual quality of the image generated by the proposed method and the method¡¦s hiding capability are good. Moreover, the mixed images produced by the proposed method are robust against attacks such as JPEG2000, JPEG, brightness adjustment, and inversion.
Robust foreground modelling to segment and detect multiple moving objects in ...IJECEIAES
Last decade has witnessed an ever increasing number of video surveillance installa- tions due to the rise of security concerns worldwide. With this comes the need for video analysis for fraud detection, crime investigation, traffic monitoring to name a few. For any kind of video analysis application, detection of moving objects in videos is a fundamental step. In this paper, an efficient foreground modelling method to segment multiple moving objects is implemented. Proposed method significantly reduces noise thereby accurately segmenting region of interest under dynamic conditions while handling occlusion to a large extent. Extensive performance analysis shows that the proposed method was found to give far better results when compared to the de facto standard as well as relatively new approaches used for moving object detection.
We presents a technique for moving objects extraction. There are several different approaches for moving object extraction, clustering is one of object extraction method with a stronger teorical foundation used in many applications. And need high performance in many extraction process of moving object. We compare K-Means and Self-Organizing Map method for extraction moving objects, for performance measurement of moving object extraction by applying MSE and PSNR. According to experimental result that the MSE value of K-Means is smaller than Self-Organizing Map. It is also that PSNR of K-Means is higher than Self-Organizing Map algorithm. The result proves that K-Means is a promising method to cluster pixels in moving objects extraction.
An unsupervised method for real time video shot segmentationcsandit
Segmentation of a video into its constituent shots is a fundamental task for indexing and
analysis in content based video retrieval systems. In this paper, a novel approach is presented
for accurately detecting the shot boundaries in real time video streams, without any a priori
knowledge about the content or type of the video. The edges of objects in a video frame are
detected using a spatio-temporal fuzzy hostility index. These edges are treated as features of the
frame. The correlation between the features is computed for successive incoming frames of the
video. The mean and standard deviation of the correlation values obtained are updated as new
video frames are streamed in. This is done to dynamically set the threshold value using the
three-sigma rule for detecting the shot boundary (abrupt transition). A look back mechanism
forms an important part of the proposed algorithm to detect any missed hard cuts, especially
during the start of the video. The proposed method is shown to be applicable for online video
analysis and summarization systems. In an experimental evaluation on a heterogeneous test set,
consisting of videos from sports, movie songs and music albums, the proposed method achieves
99.24% recall and 99.35% precision on the average.
A New Cross Diamond Search Motion Estimation Algorithm for HEVCIJERA Editor
In this project, a novel approach for motion estimation is proposed. There are few block matching algorithm existing for motion estimation. In motion estimation a new cross diamond search algorithm is implemented compared to diamond search it uses less search point. Because of this we can reduce the computational complexity. The performance of the algorithm is compared with other algorithm by means of search points. This algorithm achieves close performance than that of three step search and diamond search. Compared to all the algorithm cross diamond uses less logic elements, delay and power dissipation.
Reversible Data Hiding in the Spatial and Frequency DomainsCSCJournals
Combinational lossless data hiding in the spatial and frequency domains is proposed. In the spatial domain, a secret message is embedded in a host medium using the min-max algorithm to generate a stego-image. Subsequently, the stego-image is decomposed into the frequency domain via the integer wavelet transform (IWT). Then, a watermark is hidden in the low-high (LH) and high-low (HL) subbands of the IWT domain using the coefficient-bias approach. Simulations show that the perceptual quality of the image generated by the proposed method and the method¡¦s hiding capability are good. Moreover, the mixed images produced by the proposed method are robust against attacks such as JPEG2000, JPEG, brightness adjustment, and inversion.
Robust foreground modelling to segment and detect multiple moving objects in ...IJECEIAES
Last decade has witnessed an ever increasing number of video surveillance installa- tions due to the rise of security concerns worldwide. With this comes the need for video analysis for fraud detection, crime investigation, traffic monitoring to name a few. For any kind of video analysis application, detection of moving objects in videos is a fundamental step. In this paper, an efficient foreground modelling method to segment multiple moving objects is implemented. Proposed method significantly reduces noise thereby accurately segmenting region of interest under dynamic conditions while handling occlusion to a large extent. Extensive performance analysis shows that the proposed method was found to give far better results when compared to the de facto standard as well as relatively new approaches used for moving object detection.
We presents a technique for moving objects extraction. There are several different approaches for moving object extraction, clustering is one of object extraction method with a stronger teorical foundation used in many applications. And need high performance in many extraction process of moving object. We compare K-Means and Self-Organizing Map method for extraction moving objects, for performance measurement of moving object extraction by applying MSE and PSNR. According to experimental result that the MSE value of K-Means is smaller than Self-Organizing Map. It is also that PSNR of K-Means is higher than Self-Organizing Map algorithm. The result proves that K-Means is a promising method to cluster pixels in moving objects extraction.
SQUASHED JPEG IMAGE COMPRESSION VIA SPARSE MATRIXijcsit
To store and transmit digital images in least memory space and bandwidth image compression is needed. Image compression refers to the process of minimizing the image size by removing redundant data bits in a manner that quality of an image should not be degrade. Hence image compression reduces quantity of the image size without reducing its quality. In this paper it is being attempted to enhance the basic JPEG compression by reducing image size. The proposed technique is about amendment of the conventional run length coding for JPEG (Joint Photographic Experts Group) image compression by using the concept of sparse matrix. In this algorithm, the redundant data has been completely eliminated and hence leaving the quality of an image unaltered. The JPEG standard document specifies three steps: Discrete cosine transform, Quantization followed by Entropy coding. The proposed work aims at the enhancement of the third step which is Entropy coding.
Molecular dynamics (MD) is a very useful tool to understand various phenomena in atomistic detail. In MD, we can overcome the size- and time-scale problems by efficient parallelization. In this lecture, I’ll explain various parallelization methods of MD with some examples of GENESIS MD software optimization on Fugaku.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Data Steganography for Optical Color Image CryptosystemsCSCJournals
In this paper, an optical color image cryptosystem with a data hiding scheme is proposed. In the proposed optical cryptosystem, a confidential color image is embedded into the host image of the same size. Then the stego-image is encrypted by using the double random phase encoding algorithm. The seeds to generate random phase data are hidden in the encrypted stego-image by a content-dependent and low distortion data embedding technique. The confidential image and secret data delivery is accomplished by hiding the image into the host image and embedding the data into the encrypted stego-image. Experimental results show that the proposed data steganographic cryptosystem provides large data hiding capacity and high reconstructed image quality.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
An enhanced fireworks algorithm to generate prime key for multiple users in f...journalBEEI
This work presents a new method to enhance the performance of fireworks algorithm to generate a prime key for multiple users. A threshold technique in image segmentation is used as one of the major steps. It is used processing the digital image. Some useful algorithms and methods for dividing and sharing an image, including measuring, recognizing, and recognizing, are common. In this research, we proposed a hybrid technique of fireworks and camel herd algorithms (HFCA), where Fireworks are based on 3-dimension (3D) logistic chaotic maps. Both, the Otsu method and the convolution technique are used in the pre-processing image for further analysis. The Otsu is employed to segment the image and find the threshold for each image, and convolution is used to extract the features of the used images. The sample of the images consists of two images of fingerprints taken from the Biometric System Lab (University of Bologna). The performance of the anticipated method is evaluated by using FVC2004 dataset. The results of the work enhanced algorithm, so quick response code (QRcode) is used to generate a stream key by using random text or number, which is a class of symmetric-key algorithm that operates on individual bits or bytes.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A Survey on Block Matching Algorithms for Video Coding Yayah Zakaria
Block matching algorithm (BMA) for motion estimation (ME) is the heart to many motion-compensated video-coding techniques/standards, such as ISO MPEG-1/2/4 and ITU-T H.261/262/263/264/265, to reduce the temporal redundancy between different frames. During the last three decades,
hundreds of fast block matching algorithms have been proposed. The shape and size of search patterns in motion estimation will influence more on the searching speed and quality of performance. This article provides an overview of the famous block matching algorithms and compares their computational complexity and motion prediction quality.
An unsupervised method for real time video shot segmentationcsandit
Segmentation of a video into its constituent shots
is a fundamental task for indexing and
analysis in content based video retrieval systems.
In this paper, a novel approach is presented
for accurately detecting the shot boundaries in rea
l time video streams, without any a priori
knowledge about the content or type of the video. T
he edges of objects in a video frame are
detected using a spatio-temporal fuzzy hostility in
dex. These edges are treated as features of the
frame. The correlation between the features is comp
uted for successive incoming frames of the
video. The mean and standard deviation of the corre
lation values obtained are updated as new
video frames are streamed in. This is done to dynam
ically set the threshold value using the
three-sigma rule for detecting the shot boundary (a
brupt transition). A look back mechanism
forms an important part of the proposed algorithm t
o detect any missed hard cuts, especially
during the start of the video. The proposed method
is shown to be applicable for online video
analysis and summarization systems. In an experimen
tal evaluation on a heterogeneous test set,
consisting of videos from sports, movie songs and m
usic albums, the proposed method achieves
99.24% recall and 99.35% precision on the average
Block matching algorithm (BMA) for motion estimation is extremely normally utilized in current video coding standard like H.26x and MPEG-x as a result of its simplicity and performance and also it is a very important content in video compression the motion estimation is becoming a problem in many video applications as it to estimate the motion of the object. There are homography between 2 frames within the video sequences captured by pan-tilt (PT) cameras in their unnatural movements and therefore the geometric relationship is used to reduce the spatial redundancy in the video. In this paper, I present a homography based motion estimation algorithm and a comparative study of different algorithms. Also I introduce a unique homography-based motion for block motion estimation. This study is to provide an idea about the important tradeoff between computational complexity, result quality and various applications. This algorithm can be done on Matlab.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Real-time Moving Object Detection using SURFiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
SQUASHED JPEG IMAGE COMPRESSION VIA SPARSE MATRIXijcsit
To store and transmit digital images in least memory space and bandwidth image compression is needed. Image compression refers to the process of minimizing the image size by removing redundant data bits in a manner that quality of an image should not be degrade. Hence image compression reduces quantity of the image size without reducing its quality. In this paper it is being attempted to enhance the basic JPEG compression by reducing image size. The proposed technique is about amendment of the conventional run length coding for JPEG (Joint Photographic Experts Group) image compression by using the concept of sparse matrix. In this algorithm, the redundant data has been completely eliminated and hence leaving the quality of an image unaltered. The JPEG standard document specifies three steps: Discrete cosine transform, Quantization followed by Entropy coding. The proposed work aims at the enhancement of the third step which is Entropy coding.
Molecular dynamics (MD) is a very useful tool to understand various phenomena in atomistic detail. In MD, we can overcome the size- and time-scale problems by efficient parallelization. In this lecture, I’ll explain various parallelization methods of MD with some examples of GENESIS MD software optimization on Fugaku.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Data Steganography for Optical Color Image CryptosystemsCSCJournals
In this paper, an optical color image cryptosystem with a data hiding scheme is proposed. In the proposed optical cryptosystem, a confidential color image is embedded into the host image of the same size. Then the stego-image is encrypted by using the double random phase encoding algorithm. The seeds to generate random phase data are hidden in the encrypted stego-image by a content-dependent and low distortion data embedding technique. The confidential image and secret data delivery is accomplished by hiding the image into the host image and embedding the data into the encrypted stego-image. Experimental results show that the proposed data steganographic cryptosystem provides large data hiding capacity and high reconstructed image quality.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
An enhanced fireworks algorithm to generate prime key for multiple users in f...journalBEEI
This work presents a new method to enhance the performance of fireworks algorithm to generate a prime key for multiple users. A threshold technique in image segmentation is used as one of the major steps. It is used processing the digital image. Some useful algorithms and methods for dividing and sharing an image, including measuring, recognizing, and recognizing, are common. In this research, we proposed a hybrid technique of fireworks and camel herd algorithms (HFCA), where Fireworks are based on 3-dimension (3D) logistic chaotic maps. Both, the Otsu method and the convolution technique are used in the pre-processing image for further analysis. The Otsu is employed to segment the image and find the threshold for each image, and convolution is used to extract the features of the used images. The sample of the images consists of two images of fingerprints taken from the Biometric System Lab (University of Bologna). The performance of the anticipated method is evaluated by using FVC2004 dataset. The results of the work enhanced algorithm, so quick response code (QRcode) is used to generate a stream key by using random text or number, which is a class of symmetric-key algorithm that operates on individual bits or bytes.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A Survey on Block Matching Algorithms for Video Coding Yayah Zakaria
Block matching algorithm (BMA) for motion estimation (ME) is the heart to many motion-compensated video-coding techniques/standards, such as ISO MPEG-1/2/4 and ITU-T H.261/262/263/264/265, to reduce the temporal redundancy between different frames. During the last three decades,
hundreds of fast block matching algorithms have been proposed. The shape and size of search patterns in motion estimation will influence more on the searching speed and quality of performance. This article provides an overview of the famous block matching algorithms and compares their computational complexity and motion prediction quality.
An unsupervised method for real time video shot segmentationcsandit
Segmentation of a video into its constituent shots
is a fundamental task for indexing and
analysis in content based video retrieval systems.
In this paper, a novel approach is presented
for accurately detecting the shot boundaries in rea
l time video streams, without any a priori
knowledge about the content or type of the video. T
he edges of objects in a video frame are
detected using a spatio-temporal fuzzy hostility in
dex. These edges are treated as features of the
frame. The correlation between the features is comp
uted for successive incoming frames of the
video. The mean and standard deviation of the corre
lation values obtained are updated as new
video frames are streamed in. This is done to dynam
ically set the threshold value using the
three-sigma rule for detecting the shot boundary (a
brupt transition). A look back mechanism
forms an important part of the proposed algorithm t
o detect any missed hard cuts, especially
during the start of the video. The proposed method
is shown to be applicable for online video
analysis and summarization systems. In an experimen
tal evaluation on a heterogeneous test set,
consisting of videos from sports, movie songs and m
usic albums, the proposed method achieves
99.24% recall and 99.35% precision on the average
Block matching algorithm (BMA) for motion estimation is extremely normally utilized in current video coding standard like H.26x and MPEG-x as a result of its simplicity and performance and also it is a very important content in video compression the motion estimation is becoming a problem in many video applications as it to estimate the motion of the object. There are homography between 2 frames within the video sequences captured by pan-tilt (PT) cameras in their unnatural movements and therefore the geometric relationship is used to reduce the spatial redundancy in the video. In this paper, I present a homography based motion estimation algorithm and a comparative study of different algorithms. Also I introduce a unique homography-based motion for block motion estimation. This study is to provide an idea about the important tradeoff between computational complexity, result quality and various applications. This algorithm can be done on Matlab.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Real-time Moving Object Detection using SURFiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Framework for Soccer Video Processing and AnalysisBased on Enhanced Algorit...CSCJournals
Video contents retrieval and semantics research attract very important number of researchers in video processing and analysis domain. The researchers tries to propose structure or frameworks to extract the content of the video that's integrate many algorithms using low and high level features. The framework will be efficient if it is very simple and integrate the generic behavior. In this paper we present a framework for automatic soccer video summaries and highlights extraction using audio/video features and an enhanced generic algorithm for dominant color extraction.
Video Compression Algorithm Based on Frame Difference Approaches ijsc
The huge usage of digital multimedia via communications, wireless communications, Internet, Intranet and cellular mobile leads to incurable growth of data flow through these Media. The researchers go deep in developing efficient techniques in these fields such as compression of data, image and video. Recently, video compression techniques and their applications in many areas (educational, agriculture, medical …) cause this field to be one of the most interested fields. Wavelet transform is an efficient method that can be used to perform an efficient compression technique. This work deals with the developing of an efficient video compression approach based on frames difference approaches that concentrated on the calculation of frame near distance (difference between frames). The
selection of the meaningful frame depends on many factors such as compression performance, frame details, frame size and near distance between frames. Three different approaches are applied for removing the lowest frame difference. In this paper, many videos are tested to insure the efficiency of this technique, in addition a good performance results has been obtained.
VIDEO SEGMENTATION & SUMMARIZATION USING MODIFIED GENETIC ALGORITHMijcsa
Video summarization of the segmented video is an essential process for video thumbnails, video
surveillance and video downloading. Summarization deals with extracting few frames from each scene and
creating a summary video which explains all course of action of full video with in short duration of time.
The proposed research work discusses about the segmentation and summarization of the frames. A genetic
algorithm (GA) for segmentation and summarization is required to view the highlight of an event by
selecting few important frames required. The GA is modified to select only key frames for summarization
and the comparison of modified GA is done with the GA.
VIDEO SEGMENTATION & SUMMARIZATION USING MODIFIED GENETIC ALGORITHMijcsa
Video summarization of the segmented video is an essential process for video thumbnails, video surveillance and video downloading. Summarization deals with extracting few frames from each scene and creating a summary video which explains all course of action of full video with in short duration of time. The proposed research work discusses about the segmentation and summarization of the frames. A genetic algorithm (GA) for segmentation and summarization is required to view the highlight of an event by selecting few important frames required. The GA is modified to select only key frames for summarization and the comparison of modified GA is done with the GA.
VIDEO SEGMENTATION & SUMMARIZATION USING MODIFIED GENETIC ALGORITHMijcsa
Video summarization of the segmented video is an essential process for video thumbnails, video
surveillance and video downloading. Summarization deals with extracting few frames from each scene and
creating a summary video which explains all course of action of full video with in short duration of time.
The proposed research work discusses about the segmentation and summarization of the frames. A genetic
algorithm (GA) for segmentation and summarization is required to view the highlight of an event by
selecting few important frames required. The GA is modified to select only key frames for summarization
and the comparison of modified GA is done with the GA.
Improved Error Detection and Data Recovery Architecture for Motion Estimation...IJERA Editor
Given the critical role of motion estimation (ME) in a video coder, testing such a module is of priority concern. While focusing on the testing of ME in a video coding system, this work presents an error detection and data recovery (EDDR) design, based on the proposed residue-and-quotient (RQ) code, to embed into ME for video coding testing applications. An error in processing elements (PEs), i.e. key components of a ME, can be detected and recovered effectively by using the proposed EDDR design. Experimental results indicate that the proposed EDDR design for ME testing can detect errors and recover data with an acceptable area overhead and timing penalty. Importantly, the proposed EDDR design performs satisfactorily in terms of throughput and reliability for ME testing applications.
Dynamic Threshold in Clip Analysis and RetrievalCSCJournals
Key frame extraction can be helpful in video summarization, analysis, indexing, browsing, and retrieval. Clip analysis of key frame sequences is an open research issues. The paper deals with identification and extraction of key frames using dynamic threshold followed by video retrieval. The number of key frames to be extracted for each shot depends on the activity details of the shot. This system uses the statistics of comparison between the successive frames within a level extracted on the basis of color histograms and dynamic threshold. Two program interfaces are linked for clip analysis and video indexing and retrieval using entropy. The results using proposed system on few video sequences are tested and the extracted key frames and retrieved results are shown.
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.
Similar to A FAST SEARCH ALGORITHM FOR LARGE VIDEO DATABASE USING HOG BASED FEATURES (20)
ANALYSIS OF LAND SURFACE DEFORMATION GRADIENT BY DINSAR cscpconf
The progressive development of Synthetic Aperture Radar (SAR) systems diversify the exploitation of the generated images by these systems in different applications of geoscience. Detection and monitoring surface deformations, procreated by various phenomena had benefited from this evolution and had been realized by interferometry (InSAR) and differential interferometry (DInSAR) techniques. Nevertheless, spatial and temporal decorrelations of the interferometric couples used, limit strongly the precision of analysis results by these techniques. In this context, we propose, in this work, a methodological approach of surface deformation detection and analysis by differential interferograms to show the limits of this technique according to noise quality and level. The detectability model is generated from the deformation signatures, by simulating a linear fault merged to the images couples of ERS1 / ERS2 sensors acquired in a region of the Algerian south.
4D AUTOMATIC LIP-READING FOR SPEAKER'S FACE IDENTIFCATIONcscpconf
A novel based a trajectory-guided, concatenating approach for synthesizing high-quality image real sample renders video is proposed . The lips reading automated is seeking for modeled the closest real image sample sequence preserve in the library under the data video to the HMM predicted trajectory. The object trajectory is modeled obtained by projecting the face patterns into an KDA feature space is estimated. The approach for speaker's face identification by using synthesise the identity surface of a subject face from a small sample of patterns which sparsely each the view sphere. An KDA algorithm use to the Lip-reading image is discrimination, after that work consisted of in the low dimensional for the fundamental lip features vector is reduced by using the 2D-DCT.The mouth of the set area dimensionality is ordered by a normally reduction base on the PCA to obtain the Eigen lips approach, their proposed approach by[33]. The subjective performance results of the cost function under the automatic lips reading modeled , which wasn’t illustrate the superior performance of the
method.
MOVING FROM WATERFALL TO AGILE PROCESS IN SOFTWARE ENGINEERING CAPSTONE PROJE...cscpconf
Universities offer software engineering capstone course to simulate a real world-working environment in which students can work in a team for a fixed period to deliver a quality product. The objective of the paper is to report on our experience in moving from Waterfall process to Agile process in conducting the software engineering capstone project. We present the capstone course designs for both Waterfall driven and Agile driven methodologies that highlight the structure, deliverables and assessment plans.To evaluate the improvement, we conducted a survey for two different sections taught by two different instructors to evaluate students’ experience in moving from traditional Waterfall model to Agile like process. Twentyeight students filled the survey. The survey consisted of eight multiple-choice questions and an open-ended question to collect feedback from students. The survey results show that students were able to attain hands one experience, which simulate a real world-working environment. The results also show that the Agile approach helped students to have overall better design and avoid mistakes they have made in the initial design completed in of the first phase of the capstone project. In addition, they were able to decide on their team capabilities, training needs and thus learn the required technologies earlier which is reflected on the final product quality
PROMOTING STUDENT ENGAGEMENT USING SOCIAL MEDIA TECHNOLOGIEScscpconf
Using social media in education provides learners with an informal way for communication. Informal communication tends to remove barriers and hence promotes student engagement. This paper presents our experience in using three different social media technologies in teaching software project management course. We conducted different surveys at the end of every semester to evaluate students’ satisfaction and engagement. Results show that using social media enhances students’ engagement and satisfaction. However, familiarity with the tool is an important factor for student satisfaction.
A SURVEY ON QUESTION ANSWERING SYSTEMS: THE ADVANCES OF FUZZY LOGICcscpconf
In real world computing environment with using a computer to answer questions has been a human dream since the beginning of the digital era, Question-answering systems are referred to as intelligent systems, that can be used to provide responses for the questions being asked by the user based on certain facts or rules stored in the knowledge base it can generate answers of questions asked in natural , and the first main idea of fuzzy logic was to working on the problem of computer understanding of natural language, so this survey paper provides an overview on what Question-Answering is and its system architecture and the possible relationship and
different with fuzzy logic, as well as the previous related research with respect to approaches that were followed. At the end, the survey provides an analytical discussion of the proposed QA models, along or combined with fuzzy logic and their main contributions and limitations.
DYNAMIC PHONE WARPING – A METHOD TO MEASURE THE DISTANCE BETWEEN PRONUNCIATIONS cscpconf
Human beings generate different speech waveforms while speaking the same word at different times. Also, different human beings have different accents and generate significantly varying speech waveforms for the same word. There is a need to measure the distances between various words which facilitate preparation of pronunciation dictionaries. A new algorithm called Dynamic Phone Warping (DPW) is presented in this paper. It uses dynamic programming technique for global alignment and shortest distance measurements. The DPW algorithm can be used to enhance the pronunciation dictionaries of the well-known languages like English or to build pronunciation dictionaries to the less known sparse languages. The precision measurement experiments show 88.9% accuracy.
INTELLIGENT ELECTRONIC ASSESSMENT FOR SUBJECTIVE EXAMS cscpconf
In education, the use of electronic (E) examination systems is not a novel idea, as Eexamination systems have been used to conduct objective assessments for the last few years. This research deals with randomly designed E-examinations and proposes an E-assessment system that can be used for subjective questions. This system assesses answers to subjective questions by finding a matching ratio for the keywords in instructor and student answers. The matching ratio is achieved based on semantic and document similarity. The assessment system is composed of four modules: preprocessing, keyword expansion, matching, and grading. A survey and case study were used in the research design to validate the proposed system. The examination assessment system will help instructors to save time, costs, and resources, while increasing efficiency and improving the productivity of exam setting and assessments.
TWO DISCRETE BINARY VERSIONS OF AFRICAN BUFFALO OPTIMIZATION METAHEURISTICcscpconf
African Buffalo Optimization (ABO) is one of the most recent swarms intelligence based metaheuristics. ABO algorithm is inspired by the buffalo’s behavior and lifestyle. Unfortunately, the standard ABO algorithm is proposed only for continuous optimization problems. In this paper, the authors propose two discrete binary ABO algorithms to deal with binary optimization problems. In the first version (called SBABO) they use the sigmoid function and probability model to generate binary solutions. In the second version (called LBABO) they use some logical operator to operate the binary solutions. Computational results on two knapsack problems (KP and MKP) instances show the effectiveness of the proposed algorithm and their ability to achieve good and promising solutions.
DETECTION OF ALGORITHMICALLY GENERATED MALICIOUS DOMAINcscpconf
In recent years, many malware writers have relied on Dynamic Domain Name Services (DDNS) to maintain their Command and Control (C&C) network infrastructure to ensure a persistence presence on a compromised host. Amongst the various DDNS techniques, Domain Generation Algorithm (DGA) is often perceived as the most difficult to detect using traditional methods. This paper presents an approach for detecting DGA using frequency analysis of the character distribution and the weighted scores of the domain names. The approach’s feasibility is demonstrated using a range of legitimate domains and a number of malicious algorithmicallygenerated domain names. Findings from this study show that domain names made up of English characters “a-z” achieving a weighted score of < 45 are often associated with DGA. When a weighted score of < 45 is applied to the Alexa one million list of domain names, only 15% of the domain names were treated as non-human generated.
GLOBAL MUSIC ASSET ASSURANCE DIGITAL CURRENCY: A DRM SOLUTION FOR STREAMING C...cscpconf
The amount of piracy in the streaming digital content in general and the music industry in specific is posing a real challenge to digital content owners. This paper presents a DRM solution to monetizing, tracking and controlling online streaming content cross platforms for IP enabled devices. The paper benefits from the current advances in Blockchain and cryptocurrencies. Specifically, the paper presents a Global Music Asset Assurance (GoMAA) digital currency and presents the iMediaStreams Blockchain to enable the secure dissemination and tracking of the streamed content. The proposed solution provides the data owner the ability to control the flow of information even after it has been released by creating a secure, selfinstalled, cross platform reader located on the digital content file header. The proposed system provides the content owners’ options to manage their digital information (audio, video, speech, etc.), including the tracking of the most consumed segments, once it is release. The system benefits from token distribution between the content owner (Music Bands), the content distributer (Online Radio Stations) and the content consumer(Fans) on the system blockchain.
IMPORTANCE OF VERB SUFFIX MAPPING IN DISCOURSE TRANSLATION SYSTEMcscpconf
This paper discusses the importance of verb suffix mapping in Discourse translation system. In
discourse translation, the crucial step is Anaphora resolution and generation. In Anaphora
resolution, cohesion links like pronouns are identified between portions of text. These binders
make the text cohesive by referring to nouns appearing in the previous sentences or nouns
appearing in sentences after them. In Machine Translation systems, to convert the source
language sentences into meaningful target language sentences the verb suffixes should be
changed as per the cohesion links identified. This step of translation process is emphasized in
the present paper. Specifically, the discussion is on how the verbs change according to the
subjects and anaphors. To explain the concept, English is used as the source language (SL) and
an Indian language Telugu is used as Target language (TL)
EXACT SOLUTIONS OF A FAMILY OF HIGHER-DIMENSIONAL SPACE-TIME FRACTIONAL KDV-T...cscpconf
In this paper, based on the definition of conformable fractional derivative, the functional
variable method (FVM) is proposed to seek the exact traveling wave solutions of two higherdimensional
space-time fractional KdV-type equations in mathematical physics, namely the
(3+1)-dimensional space–time fractional Zakharov-Kuznetsov (ZK) equation and the (2+1)-
dimensional space–time fractional Generalized Zakharov-Kuznetsov-Benjamin-Bona-Mahony
(GZK-BBM) equation. Some new solutions are procured and depicted. These solutions, which
contain kink-shaped, singular kink, bell-shaped soliton, singular soliton and periodic wave
solutions, have many potential applications in mathematical physics and engineering. The
simplicity and reliability of the proposed method is verified.
AUTOMATED PENETRATION TESTING: AN OVERVIEWcscpconf
The using of information technology resources is rapidly increasing in organizations,
businesses, and even governments, that led to arise various attacks, and vulnerabilities in the
field. All resources make it a must to do frequently a penetration test (PT) for the environment
and see what can the attacker gain and what is the current environment's vulnerabilities. This
paper reviews some of the automated penetration testing techniques and presents its
enhancement over the traditional manual approaches. To the best of our knowledge, it is the
first research that takes into consideration the concept of penetration testing and the standards
in the area.This research tackles the comparison between the manual and automated
penetration testing, the main tools used in penetration testing. Additionally, compares between
some methodologies used to build an automated penetration testing platform.
CLASSIFICATION OF ALZHEIMER USING fMRI DATA AND BRAIN NETWORKcscpconf
Since the mid of 1990s, functional connectivity study using fMRI (fcMRI) has drawn increasing
attention of neuroscientists and computer scientists, since it opens a new window to explore
functional network of human brain with relatively high resolution. BOLD technique provides
almost accurate state of brain. Past researches prove that neuro diseases damage the brain
network interaction, protein- protein interaction and gene-gene interaction. A number of
neurological research paper also analyse the relationship among damaged part. By
computational method especially machine learning technique we can show such classifications.
In this paper we used OASIS fMRI dataset affected with Alzheimer’s disease and normal
patient’s dataset. After proper processing the fMRI data we use the processed data to form
classifier models using SVM (Support Vector Machine), KNN (K- nearest neighbour) & Naïve
Bayes. We also compare the accuracy of our proposed method with existing methods. In future,
we will other combinations of methods for better accuracy.
VALIDATION METHOD OF FUZZY ASSOCIATION RULES BASED ON FUZZY FORMAL CONCEPT AN...cscpconf
In order to treat and analyze real datasets, fuzzy association rules have been proposed. Several
algorithms have been introduced to extract these rules. However, these algorithms suffer from
the problems of utility, redundancy and large number of extracted fuzzy association rules. The
expert will then be confronted with this huge amount of fuzzy association rules. The task of
validation becomes fastidious. In order to solve these problems, we propose a new validation
method. Our method is based on three steps. (i) We extract a generic base of non redundant
fuzzy association rules by applying EFAR-PN algorithm based on fuzzy formal concept analysis.
(ii) we categorize extracted rules into groups and (iii) we evaluate the relevance of these rules
using structural equation model.
PROBABILITY BASED CLUSTER EXPANSION OVERSAMPLING TECHNIQUE FOR IMBALANCED DATAcscpconf
In many applications of data mining, class imbalance is noticed when examples in one class are
overrepresented. Traditional classifiers result in poor accuracy of the minority class due to the
class imbalance. Further, the presence of within class imbalance where classes are composed of
multiple sub-concepts with different number of examples also affect the performance of
classifier. In this paper, we propose an oversampling technique that handles between class and
within class imbalance simultaneously and also takes into consideration the generalization
ability in data space. The proposed method is based on two steps- performing Model Based
Clustering with respect to classes to identify the sub-concepts; and then computing the
separating hyperplane based on equal posterior probability between the classes. The proposed
method is tested on 10 publicly available data sets and the result shows that the proposed
method is statistically superior to other existing oversampling methods.
CHARACTER AND IMAGE RECOGNITION FOR DATA CATALOGING IN ECOLOGICAL RESEARCHcscpconf
Data collection is an essential, but manpower intensive procedure in ecological research. An
algorithm was developed by the author which incorporated two important computer vision
techniques to automate data cataloging for butterfly measurements. Optical Character
Recognition is used for character recognition and Contour Detection is used for imageprocessing.
Proper pre-processing is first done on the images to improve accuracy. Although
there are limitations to Tesseract’s detection of certain fonts, overall, it can successfully identify
words of basic fonts. Contour detection is an advanced technique that can be utilized to
measure an image. Shapes and mathematical calculations are crucial in determining the precise
location of the points on which to draw the body and forewing lines of the butterfly. Overall,
92% accuracy were achieved by the program for the set of butterflies measured.
SOCIAL MEDIA ANALYTICS FOR SENTIMENT ANALYSIS AND EVENT DETECTION IN SMART CI...cscpconf
Smart cities utilize Internet of Things (IoT) devices and sensors to enhance the quality of the city
services including energy, transportation, health, and much more. They generate massive
volumes of structured and unstructured data on a daily basis. Also, social networks, such as
Twitter, Facebook, and Google+, are becoming a new source of real-time information in smart
cities. Social network users are acting as social sensors. These datasets so large and complex
are difficult to manage with conventional data management tools and methods. To become
valuable, this massive amount of data, known as 'big data,' needs to be processed and
comprehended to hold the promise of supporting a broad range of urban and smart cities
functions, including among others transportation, water, and energy consumption, pollution
surveillance, and smart city governance. In this work, we investigate how social media analytics
help to analyze smart city data collected from various social media sources, such as Twitter and
Facebook, to detect various events taking place in a smart city and identify the importance of
events and concerns of citizens regarding some events. A case scenario analyses the opinions of
users concerning the traffic in three largest cities in the UAE
SOCIAL NETWORK HATE SPEECH DETECTION FOR AMHARIC LANGUAGEcscpconf
The anonymity of social networks makes it attractive for hate speech to mask their criminal
activities online posing a challenge to the world and in particular Ethiopia. With this everincreasing
volume of social media data, hate speech identification becomes a challenge in
aggravating conflict between citizens of nations. The high rate of production, has become
difficult to collect, store and analyze such big data using traditional detection methods. This
paper proposed the application of apache spark in hate speech detection to reduce the
challenges. Authors developed an apache spark based model to classify Amharic Facebook
posts and comments into hate and not hate. Authors employed Random forest and Naïve Bayes
for learning and Word2Vec and TF-IDF for feature selection. Tested by 10-fold crossvalidation,
the model based on word2vec embedding performed best with 79.83%accuracy. The
proposed method achieve a promising result with unique feature of spark for big data.
GENERAL REGRESSION NEURAL NETWORK BASED POS TAGGING FOR NEPALI TEXTcscpconf
This article presents Part of Speech tagging for Nepali text using General Regression Neural
Network (GRNN). The corpus is divided into two parts viz. training and testing. The network is
trained and validated on both training and testing data. It is observed that 96.13% words are
correctly being tagged on training set whereas 74.38% words are tagged correctly on testing
data set using GRNN. The result is compared with the traditional Viterbi algorithm based on
Hidden Markov Model. Viterbi algorithm yields 97.2% and 40% classification accuracies on
training and testing data sets respectively. GRNN based POS Tagger is more consistent than the
traditional Viterbi decoding technique.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
2. 36 Computer Science & Information Technology (CS & IT)
Many video search algorithms [7]-[10] have been proposed, and achieves successes to a certain
extent. But such algorithms, however, are computational-power hungry for the exhaustive search
of large video database. For large video database, Search speed is an important issue of video
search. Base on active search [4], a temporal pruning algorithm, Kashino et al. [1] improved the
conventional multimedia search algorithm. Nevertheless, their feature extraction utilizes intensity
features of the frame image, so the results may be sensitive to small change of luminance and
motion in the frame. In this paper, we utilizes a new feature based on Histogram of Oriented
Gradients (HOG) [5] features, which had been reliably applied to object detection, especially
pedestrian detection [6][11]. It has the following advantages: computational simplicity, motion-
insensitivity and luminance-insensitivity. Because such a feature is compatible with active search
algorithm, fast search speed can also be achieved by combining HOG based features and active
search.
Figure 1. Processing steps of HOG based features.
In section 2, we will first introduce HOG based features, and then describe fast video search
algorithm we employ in section 3. Experimental results compared to conventional search
approach will be discussed in section 4. Finally, conclusions are given in section 5.
2. HOG BASED FEATURES
Histogram of Oriented Gradients (HOG) [5] features has been developed for object recognition
previously. Figure 1 shows the processing steps of HOG based features. In HOG, for each pixel
of an input image, the intensity difference of the horizontally adjacent pixels (fx) and the intensity
difference of the vertically adjacent pixels (fy) are first calculated by using simple subtraction
operations shown as formula (1), (2).
݂ݕ = ݂ሺ݅, ݆ + 1ሻ − ݂ሺ݅, ݆ − 1ሻ (1)
݂ݔ = ݂ሺ݅ + 1, ݆ሻ − ݂ሺ݅ − 1, ݆ሻ (2)
ߙ = ݊ܽݐିଵ ௬
௫
(3)
Each intensity variation vector is then quantized simply by the oriented angle calculated by
formula (3). The number of vectors quantized in each quantization region is counted and a
histogram is generated.
3. Computer Science & Information Technology (CS & IT) 37
The essence of HOG based features above can be considered that the operation detects and
quantizes the direction of intensity variation in the image blocks. Hence HOG based features
contain very effective image feature information. We will describe how to apply it as feature
vector of frame to solving the fast video search problem in next section.
3. PROPOSED VIDEO SEARCH ALGORITHM
The procedure of proposed fast search algorithm is shown in figure 2. In the pre-processing stage,
the feature vectors are calculated from the query video clip and the video database HOG method
described in section 2. The feature vectors are then quantized using VQ algorithm which applied
quantization by combinations of scalar quantization (SVQ) for each feature dimension [1]. In the
search stage, the windows are applied to both the query feature vectors and the feature vectors of
video database. In the next step, the number of vectors quantized in the windows of the query
video clip and video database are counted and feature vector histograms are created respectively.
The similarity between these histograms is then calculated. If the similarity exceeded a threshold
value given previously, the query video clip will be detected and located. Otherwise, the window
on the video database will be skipped to the next position determined by the similarity in current
position and the threshold value. In the last step, the window on the video database is shifted
forward in time and the search proceeds.
Figure 2. The procedure of proposed fast search algorithm
Here, histogram intersection is used as the similarity measure [4], and is defined as formula (4).
∑=
=
=
L
l
DlQl
DQQD
hh
N
HHSS
1
),min(
1
),(
(4)
4. 38 Computer Science & Information Technology (CS & IT)
where hQl, hDl are the numbers of feature vectors contained in the l-th bin of the histograms for
the query and the stored signal, respectively, L is the number of histogram bins, and N is the total
number of feature vectors contained in the histogram. The skip width w is shown by formula (5).
<+−
=
otherwise
SSNfloor
w QDQD
1
)(1))(( θθ
(5)
where floor(x) means the greatest integral value less than x, and θ is a given threshold.
4. EXPERIMENTAL RESULTS AND DISCUSSIONS
We performed all of the experiments on a conventional PC @ 3.2GHz (4G memory). The
algorithm was implemented in ANSI C. We used 6 hours of video captured from TV program. In
the experiment, the video frame rate was 14.97 fps, and image size was 80*60 as shown in table
I.
Tabel I: Parameters of Video dataset.
Video content News, drama, sports etc.
Video length
Query video clips: 15s * 200
Video database sequence: 6 hours
Frame rate 14.98 fps
Frame number
Query video clips: 15s * 200
Video database sequence: 6 hours
Image format PPM
Capture size 80*60
We captured 6 hours of video twice, one for video database sequence and the other for query
video clips. Query video clips were generated by selecting video clips randomly for 200 times
from the second video. Then we can perform search for 200 video clips from 6 hours of video.
The threshold θ is 0.7 determined by preparing experiments according to FAR and FRR curve,
which will be discussed later.
We utilized a 1-hour video sequence by selecting randomly from the second video to determine
boundary threshold which were used to implement scalar VQ process (SVQ).
To suit the search task, quantization levels of HOG are set at 8 in θ -axis (totally 9) in the feature
extraction stage. Thus, the number of histogram bins is total 512. Similarity calculation between
the feature vector histograms will be quite faster compared with conventional algorithm which
number of histogram bins is 4096.
4.1. Image Features of Conventional Algorithm
In conventional algorithm [1], they use small scaled images as video features. An image feature
vector is defined as formula (6).
))(,)(,),(()( 1 kgkgkgkg Wj ⋅⋅⋅⋅⋅⋅= (6)
5. Computer Science & Information Technology (CS & IT) 39
where k is the frame number, j is the division number of the subimages, and W is the number of
subimages. The gj(k) is the normalized intensity and is defined as formula (7), where )(kx j is the
average intensity in the j-th subsection.
)(min)(max
)(min)(
)(
kxkx
kxkx
kg
i
i
i
i
i
i
j
j
−
−
= (7)
Figure 3. The example of search result.
4.2. Experimental Results
Figure 3 shows an example of result in 200 times search. The red ellipse marks the correct
location of detected query video clip. Results of search accuracy are shown in figure 4. Search
accuracy is shown as a function of window size. The perfect accuracy of 100% is obtained when
window size is given 30sec. But even if window size decreases to 2sec, the accuracy still remains
98%.
We also compared our algorithm with the algorithm which does not utilize active search (full
search), and conventional fast search algorithm described in section 4.1. Table II gives the
approximate computational cost of the algorithms. As descried above, the number of histogram
bins is total 512 in our proposed algorithm, 8 times smaller than that of conventional algorithm.
From Table I, we can see the search time costs only 70ms, which is 271 times faster than full
search, and also 6.7 times faster than the conventional fast search algorithm.
We also investigated the robustness of image features used in respective algorithms by adding
Gaussian noise to the query video clips. Figure 5 shows how the search accuracy changes with
the amount of noises. The curves with trigonal mark and foursquare mark stand for proposed
algorithm and conventional algorithm, respectively. Our proposed algorithm achieves higher
search accuracy than conventional algorithm. Although the search accuracy decreases with
6. 40 Computer Science & Information Technology (CS & IT)
increase the amount of Gaussian noises, it can be said that proposed algorithm is more robust for
video search task than the conventional approach.
Table I: Approximate Computational Cost (CPU time).
Stage Full search Conventional Proposed algorithm
Feature Extraction 540sec 540sec 550sec
VQ processing 50ms 50ms 35ms
Search 19sec 470ms 70ms
Figure 5. Gaussian noise vs search accuracy.
Figure 4. Window size vs. search
5. CONCLUSIONS
By using a new feature based on HOG based features, we present a fast and robust video search
algorithm for video clips from large video database. The proposed search algorithm has been
7. Computer Science & Information Technology (CS & IT) 41
evaluated by 6 hours of video to search for 200 video clips. Experimental results show that search
time costs only 70ms, which is 271 times faster than full search, and also 6.7 times faster than the
conventional fast search algorithm. Furthermore, proposed algorithm is more robust against
Gaussian noise for video search task than the conventional approach.
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