Image and Video Analytics detailed syllabus for Artificial Intelligence & Data Science (AI&DS) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the AI&DS 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 Artificial Intelligence & Data Science 5th Sem scheme and its subjects, do visit AI&DS 5th Sem 2021 regulation scheme. For Professional Elective-I scheme and its subjects refer to AI&DS 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 pre-processing 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 architecture-Improvement 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 Artificial Intelligence & Data Science 5th Sem, visit AI&DS 5th Sem subject syllabuses for 2021 regulation.
For all Artificial Intelligence & Data Science results, visit Anna University AI&DS all semester results direct link.