Information

Instructor: Professor R. Venkatesh Babu and Professor Anirban Chakraborty
Classroom Venue: Room 202, CDS
Class Timings: Monday and Wednesday, 12PM to 1:15PM.

Brief description of the course

The goal of machine vision is to develop methods that enable a machine to “understand” or analyze images and videos. This course will address the research issues towards developing algorithms that can perform high-level visual recognition tasks on real-world images and videos. This course will review and discuss current approaches to high-level visual recognition problems, such as background modeling, object recognition and categorization, tracking, scene understanding, human motion understanding, etc. This course is intended for graduate level students.

Prerequisites

Primary crucial prerequisites : Image Processing

Secondary Prerequisites(familiarity preffered): Statistics and Linear Algebra.

Course Outcomes

  1. Thoroughly Understanding the fundamentals of Video analytics.
  2. Gaining Knowlegde about State-of the art models and Other Important Works in recent years.
  3. Learning the skills to implement computer vision Systems(Use of Multiple packages etc.)