EC8010 - VIDEO ANALYTICS (Syllabus) 2017-regulation Anna University
EC8010 - VIDEO ANALYTICS (Syllabus) 2017-regulation Anna University
EC8010 |
VIDEO ANALYTICS |
LPTC |
---|
3003
OBJECTIVES:The student should be made:
• To understand the need for video Analytics
• To understand the basic configuration of video analytics
• To understand the functional blocks of a video analytic system
• To get exposed to the various applications of video analytics
• To understand the basic configuration of video analytics
• To understand the functional blocks of a video analytic system
• To get exposed to the various applications of video analytics
UNIT I |
VIDEO ANALYTIC COMPONENTS |
9 |
---|
Need for Video Analytics-Overview of video Analytics- Foreground extraction- Feature extraction- classifier - Preprocessing- edge detection- smoothening- Feature space-PCA-FLD-SIFT features
UNIT II |
FOREGROUND EXTRACTION |
9 |
---|
Background estimation- Averaging- Gaussian Mixture Model- Optical Flow based- Image Segmentation- Region growing- Region splitting-Morphological operations- erosion-Dilation- Tracking in a multiple camera environment
UNIT III |
CLASSIFIERS |
9 |
---|
Neural networks (back propagation) - Deep learning networks- Fuzzy Classifier- Bayesian classifier-HMM based classifier
UNIT IV |
VIDEO ANALYTICS FOR SECURITY |
9 |
---|
Abandoned object detection- human behavioral analysis -human action recognition- perimeter security- crowd analysis and prediction of crowd congestion
UNIT V |
VIDEO ANALYTICS FOR BUSINESS INTELLIGENCE & TRAFFIC MONITIRING AND ASSISTANCE |
9 |
---|
Customer behavior analysis - people counting- Traffic rule violation detection- traffic congestion identification for route planning- driver assistance- lane change warning
TOTAL : 45 PERIODS
OUTCOMES:At the end of the course, the student should be able to:
• Design video analytic algorithms for security applications
• Design video analytic algorithms for business intelligence
• Design custom made video analytics system for the given target application
• Design video analytic algorithms for business intelligence
• Design custom made video analytics system for the given target application
REFERENCES
1. Graeme A. Jones (Editor), Nikos Paragios (Editor), Carlo S. Regazzoni (Editor) Video-Based Surveillance Systems: Computer Vision and Distributed Processing , Kluwer academic publisher, 2001
2. Nilanjan Dey (Editor), Amira Ashour (Editor) and Suvojit Acharjee (Editor), Applied Video Processing in Surveillance and Monitoring Systems (IGI global) 2016
3. Zhihao Chen (Author), Ye Yang (Author), Jingyu Xue (Author), Liping Ye (Author), Feng Guo (Author), The Next Generation of Video Surveillance and Video Analytics: The Unified Intelligent Video Analytics Suite, CreateSpace Independent Publishing Platform, 2014
4. Caifeng Shan (Editor), Fatih Porikli (Editor), Tao Xiang (Editor), Shaogang Gong (Editor) Video Analytics for Business Intelligence, Springer, 2012
2. Nilanjan Dey (Editor), Amira Ashour (Editor) and Suvojit Acharjee (Editor), Applied Video Processing in Surveillance and Monitoring Systems (IGI global) 2016
3. Zhihao Chen (Author), Ye Yang (Author), Jingyu Xue (Author), Liping Ye (Author), Feng Guo (Author), The Next Generation of Video Surveillance and Video Analytics: The Unified Intelligent Video Analytics Suite, CreateSpace Independent Publishing Platform, 2014
4. Caifeng Shan (Editor), Fatih Porikli (Editor), Tao Xiang (Editor), Shaogang Gong (Editor) Video Analytics for Business Intelligence, Springer, 2012
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