Image and Video Analytics detailed syllabus for Computer & Communication Engineering (CCE) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the CCE students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Computer & Communication Engineering 5th Sem scheme and its subjects, do visit CCE 5th Sem 2021 regulation scheme. For Professional Elective-I scheme and its subjects refer to CCE Professional Elective-I syllabus scheme. The detailed syllabus of image and video analytics is as follows.
Course Objectives:
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Unit I
INTRODUCTION
Computer Vision – Image representation and image analysis tasks – Image representations -digitization – properties – color images – Data structures for Image Analysis – Levels of image data representation – Traditional and Hierarchical image data structures.
Unit II
IMAGE PRE-PROCESSING
Local pre-processing – Image smoothing – Edge detectors – Zero-crossings of the second derivative – Scale in image processing – Canny edge detection – Parametric edge models – Edges in multi-speralct images – Local pre-processing in the frequency domain – Line detection by local preprocessing operators – Image restoration.
Unit III
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Unit IV
FACE RECOGNITION AND GESTURE RECOGNITION
Face Recognition-Introduction-Applications of Face Recognition-Process of Face RecognitionDeepFace solution by Facebook-FaceNet for Face Recognition- Implementation using FaceNet-Gesture Recognition.
Unit V
VIDEO ANALYTICS
Video Processing – use cases of video analytics-Vanishing Gradient and exploding gradient problem-RestNet architecture-RestNet and skip connections-Inception Network-GoogleNet architectureImprovement in Inception v2-Video analytics-RestNet and Inception v3.
List of Exercises
- Write a program that computes the T-pyramid of an image.
- Write a program that derives the quad tree representation of an image using the homogeneity criterion of equal intensity
- Develop programs for the following geometric transforms: (a) Rotation (b) Change of scale (c) Skewing (d) Affine transform calculated from three pairs of corresponding points (e) Bilinear transform calculated from four pairs of corresponding points.
- Develop a program to implement Object Detection and Recognition
- Develop a program for motion analysis using moving edges, and apply it to your image sequences.
- Develop a program for Facial Detection and Recognition
- Write a program for event detection in video surveillance system
Course Outcomes:
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Text Books:
- Milan Sonka, Vaclav Hlavac, Roger Boyle, “Image Processing, Analysis, and Machine Vision”, 4nd edition, Thomson Learning, 2013.
- Vaibhav Verdhan,(2021, Computer Vision Using Deep Learning Neural Network Architectures with Python and Keras,Apress 2021(UNIT-III,IV and V)
Reference Books:
- Richard Szeliski, “Computer Vision: Algorithms and Applications”, Springer Verlag London Limited,2011.
- Caifeng Shan, FatihPorikli, Tao Xiang, Shaogang Gong, “Video Analytics for Business Intelligence”, Springer, 2012.
- D. A. Forsyth, J. Ponce, “Computer Vision: A Modern Approach”, Pearson Education, 2003.
- E. R. Davies, (2012), “Computer & Machine Vision”, Fourth Edition, Academic Press.
For detailed syllabus of all the other subjects of Computer & Communication Engineering 5th Sem, visit CCE 5th Sem subject syllabuses for 2021 regulation.
For all Computer & Communication Engineering results, visit Anna University CCE all semester results direct link.