AID-565, Computer Vision

Spring 2023-24


Instructor: Balasubramanian Raman
Other Instructors: Alok Bhardwaj and Sanjeev Kumar
Office: S-227, CSE Building
Class Meeting Time: Mondays, Wednesdays (10:00-10:55 am), Thursdays (11:00-11:55 a.m).
Class Room: Gargi Block - 312
Office Hours: Tuesdays, Fridays 11:00 a.m. - 1:00 p.m. and by appointment
TAs: Dr. Pradeep Singh (pradeep.cs at sric) (Post Doc), Srishti Yadav (srishti_y at mfs), Deepak Kumar (d_kumar@cs)(PhD students), Darpan (darpan_s at mfs) and Rahul (rahul_k at mfs) (M.Tech students)
Email: first four letters of first name at cs dot ac dot in

Announcements

January 17, 2024: Tutorials have begun.
January 05, 2024: First session of classes have begun (14 lectures by R. Balasubramanian).

Course Objectives, Learning Outcomes and Prerequisites

To provide a glimpse of what computer vision is about
To give an understanding of image processing for computer vision
To know about Image formation and camera calibration
To impart the knowledge on Feature detection and matching

Course Outcomes:
After completing the course you will be able to:
identify basic concepts, terminology, theories, models and methods in the field of computer vision,
describe known principles of human visual system,
describe basic methods of computer vision related to multi-scale representation, edge detection and detection of other primitives, stereo, motion and object recognition,
suggest a design of a computer vision system for a specific problem

Prerequisites: NIL.

Evaluation Components


Lecture Notes

01. Introduction to Computer Vision (08/01/2024)
02. Field of View, Stereo Vision and Reconstruction of 3D primitives from Stereo & sequence of Images (10/01/2024)
03. Reconstruction of 3D primitives from Stereo and sequence of Images, 3D Plane and a Straight line (11/01/2024)
04. Basic Transformations and Viewing in 3D (15/01/2024)
05. Parallel Projections, Geometric Camera Parameters and Extrinsic & Intrinsic camera parameters (17/01/2024)
06. Epipolar Geometry and camera parameters (19/01/2024)
07. Derivations of Extrinsic and Intrinsic camera parameters- Direct and Indirect Methods (24/01/2024)
08. Image Enhancement (25/01/2024)
09. Spatial Filtering (29/01/2024)
10. Edge Detectors and Introduction to Fourier Transform (30/01/2024, Extra Class 11 am to 12 noon, LHC 002)
11. Low Pass and High Pass Filters (31/01/2024)
12. Fractional Fourier Transform, LoG and Canny Edge Detectors (01/02/2024)
13. Quiz, Tentative Solutions (05/02/2024)

Assignments


01. Assignment 1 (Posted on 17/01/2024, Deadline 31/01/2024)
02. Assignment 2 (Posted on 25/01/2024, Deadline 21/02/2024)
03. Assignment 3 (Posted on 06/02/2024, Deadline 05/03/2024)


Examinations



Recommended Study Material

The following will be used as a reference/text book for this course:
1. Forsyth, D. A. and Ponce, J., "Computer Vision: A Modern Approach",Prentice Hall, 2nd Ed, 2011.
2. Gonzalez, R. C. and Woods, R. E., "Digital Image Processing", Prentice Hall, 3rd Ed., 2009.