Computer Vision

Computer Vision (BCE7518): Syllabus

Unit-I Introduction:

Computer Vision, 2D/3D Vision, Filters, Binary Images, Features, Texture, Shape, Segmentation, Model Fitting and Probabilistic Models representation, color spaces. Case Study - 2D to 3D image conversion.

Unit-II Image Processing and Feature Extraction:

 Image Formation, Image Filtering, Edge Detection, Principal Component Analysis, Corner Detection, SIFT, SURF. Case Study - How Tesla uses Cameras and Computer Vision to detect cars for its self-driving mode.

Unit-III Neural Network for Computer Vision:

 Neural Network, Introduction of CNN for Image Recognition- Kernel, Padding, Aggregation, Feature Map, Activation Functions. Case Study - Sparrow - An Autonomous Surveillance by Percepto.

Unit-IV Object Detection & Recognition :

Detection methods – Histogram of Oriented Gradients (HOG), Region-based Convolutional Neural Networks (R-CNN), Hough transforms and other simple object recognition methods, Generative Adversarial Networks (GANs). Case Study - Face Frontal View Generation.