JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

Course Outcomes:

• Understand the algorithms available for performing analysis on video data and address the challenges
• Understand the approaches for identifying and tracking objects and person with motion-based algorithms.
• Understand the algorithms available for searching and matching in video content
• Analyze approaches for action representation and recognition
• Identify, Analyze and apply algorithms for developing solutions for real world problems

UNIT - I

Introduction: Video Analytics. Computer Vision: Challenges- Spatial Domain Processing – Frequency Domain Processing-Background Modeling-Shadow Detection-Eigen Faces - Object Detection -Local Features-Mean Shift: Clustering, Tracking - Object Tracking using Active Contours –

UNIT - II

Tracking & Video Analysis: Tracking and Motion Understanding – Kalman filters, condensation, particle, Bayesian filters, hidden Markov models, change detection and model-based tracking- Motion estimation and Compensation-Block Matching Method, Hierarchical Block Matching,

UNIT - III

Overlapped Block Motion and compensation, Pel-Recursive Motion Estimation, Mesh Based Method, Optical Flow Method - Motion Segmentation -Thresholding for Change Detection, Estimation of Model parameters - Optical Flow Segmentation-Modified Hough Transform Method-

UNIT - IV

Segmentation for Layered Video Representation-Bayesian Segmentation -Simultaneous Estimation and Segmentation-Motion Field Model – Action Recognition - Low Level Image Processing for Action Recognition: Segmentation and Extraction, Local Binary Pattern, Structure from Motion –

UNIT - V

Action Representation Approaches: Classification of Various Dimension of Representation, View Invariant Methods, Gesture Recognition and Analysis, Action Segmentation. Case Study: Face Detection and Recognition, Natural Scene Videos, Crowd Analysis, Video Surveillance, Traffic Monitoring, Intelligent Transport System.

Text Books/References:

• 1. Richard Szeliski, “Computer Vision: Algorithms and Applications”, Springer, 2011.
• 2. Yao Wang, JornOstermann and Ya-Qin Zhang, “Video Processing and Communications”, Prentice Hall, 2001.
• 3. A.MuratTekalp, “Digital Video Processing”, Pearson, 1995
• 4. Thierry Bouwmans, FatihPorikli, Benjamin Höferlin and Antoine Vacavant, “Background Modeling and Foreground Detection for Video Surveillance: Traditional and Recent Approaches, Implementations, Benchmarking and Evaluation", CRC Press, Taylor and Francis Group, 2014. R19 M. TECH. CN/CNIS/CYBER SECURITY
• 5. Md. Atiqur Rahman Ahad, "Computer Vision and Action Recognition-A Guide for Image Processing and Computer Vision Community for Action Understanding", Atlantis Press, 2011. R19 M. TECH. CN/CNIS/CYBER SECURITY M. Tech. (CNIS/CN/Cyber Security) – II Year – I Semester Common to CNIS, CN and Cyber Security