Course Description: This course offers a comprehensive introduction to the field of computer vision, focusing on how computers can be designed to interpret and understand visual information from the world. Students will explore various techniques and algorithms used to process and analyze images and video, with applications ranging from autonomous vehicles to medical imaging.
Key Topics Covered:
Introduction to Computer Vision: Overview of the field, its history, and key applications.
Image Processing Fundamentals: Techniques for image enhancement, filtering, and transformation.
Feature Extraction: Methods for detecting and describing features such as edges, corners, and blobs.
Object Detection and Recognition: Algorithms for identifying and classifying objects within images.
Motion Analysis: Techniques for tracking and analyzing movement in video sequences.
Deep Learning for Computer Vision: Application of neural networks and deep learning frameworks to vision tasks.
Prerequisites: Basic knowledge of programming and linear algebra.
Course Format: Lectures, practical exercises, and project work.
Link to Instructional Media and Materials:
https://classroom.google.com/u/1/c/NzczNDQyMzIxNTI0 (Section-1)
https://classroom.google.com/u/1/c/NzkwNDk0Nzg2Njg3 (Section-2)