E1 216 : Computer Vision 3:1
(Jan - Apr 2015)

Course Instructors Prof. K. R. Ramakrishnan
Email ID krr [at] ee [dot] iisc [dot] ernet [dot] in
Address Room No: 218A, Electrical Department, IISc.
Phone 2293 2441 and 2293 2572
Course Timings Monday & Wednesday - 2:00PM to 3:30PM
Venue PE - 218, Electrical Department
Pre-requisite Knowledge of MATLAB and OpenCV

Camera Calibration Lecture Slides posted


Course Syllabus

This course will present a broad, introductory survey intended to develop familiarity with the approaches to modeling and solving problems in computer vision. Mathematical modeling and algorithmic solutions for vision tasks will be emphasised. Image formation: camera geometry, radiometry, colour; Image features : points, lines, edges, contours, texture; Shape : object geometry, stereo, shape from cues; Motion : calibration, registration, Multiview geometry, optical Flow; approaches to grouping and segmentation; representation and methods for object recognition; applications



References:

1) David A. Forsyth and Jean Ponce, Computer Vision: A Modern Approach, Pearson Education, 2003
2) Richard Szeliski, Computer vision: algorithms and applications. Springer, 2010.
3) Richard Hartley and Andrew Zisserman. Multiple view geometry in computer vision. Cambridge university press, 2003.
4) Current Literature
5) Resources and Links Page of Forsyth and Ponce textbook



Lectures and Handouts



Lecture Series 3:

Slides :
  1. Slides and Other Materials

References:
  1. Chapter 2 of Forsyth and Ponce

Courtesy:
  1. Lecture Slides of Dr. Venu Madhav Govindu, EE, IISc.
  2. Jim Bethel's notes on Rotation Matrices: CE503 - Photogrammetry I
  3. Prof. Trevor Darrell's lecture slides on Image Formation, Computer Vision (CS280), UCB

Note: The links in the slides work only when the other documents are present in the same folder. So kindly ensure the slides and the other two documents are placed in the same folder.

Lecture Series 4 - Stereo:

Slides :
  1. Stereo
  2. Two-view Geometry
  3. Epipolar Geometry

Courtesy:
  1. Slides on Epipolar Geometry from CS143 Introduction to Computer Vision by Michael J. Black, Brown University

Lecture Series 5 - Camera Calibration:

Slides :
  1. Slides

Courtesy:
  1. Slides on Camera Calibration by Dr. Venu Madhav Govindu, EE, IISc.

Suggested Readings:
  1. Rusinkiewicz, Szymon, and Marc Levoy. "Efficient variants of the ICP algorithm." 3-D Digital Imaging and Modeling, 2001. Proceedings. Third International Conference on. IEEE, 2001. Paper Link
  2. Umeyama, Shinji. "Least-squares estimation of transformation parameters between two point patterns." IEEE Transactions on pattern analysis and machine intelligence 13.4 (1991): 376-380. Paper Link


Homework and Assignments

Useful Links