16-385 Computer Vision
Instructor: Kris Kitani
Time: Tuesday, Thursday 12:00PM - 1:20PM
Location: WEAN HALL 5403
Course Description

This course provides a comprehensive introduction to computer vision. Major topics include image processing, detection and recognition, geometry-based and physics-based vision and video analysis. Students will learn basic concepts of computer vision as well as hands on experience to solve reallife vision problems.

This course requires familarity with linear algebra and basic probability. MATLAB will be used for project assignments and will be covered as part of the introduction to the course.

Prerequisites: (18202 and 15122) or (21240 and 21241 and 21259 and 15122).

Teaching Assistants
Recommended Textbook

We use Piazza for class discussion and announments.


There are five individual projects and one midterm exam. There is no final exam.

Project 1Hough Transform15%
Project 2Bag of Words15%
Project 3Homography20%
Project 4Structure from Motion20%
Project 5Tracking20%
Midterm Exam10%

These lecture notes have been pieced together from many different people and places. Special thanks to colleagues for sharing their PPTs directly with me: Bob Collins, Srinivasa Narashiman, Martial Hebert, Alyosha Efros, Ali Faharadi. I would also like to thank the following people for making their lecture notes and materials available online: Steve Seitz, Richard Selinsky, Larry Zitnick, Noah Snavely, Lana Lazebnik, Kristen Grauman, Yung-Yu Chuang, T. Tuytelaars, Fei-Fei Li, Antonio Torralba, Rob Fergus, David Claus and Dan Jurafsky.

Image Processing
Jan 13
Jan 15
Jan 20
Programming Tutorial
Jan 22
Jan 27
Jan 29
Feb 03
Project 1 Due on Feb 3
Feb 05
Feb 10
Feb 12
Feb 17
Feb 19
Feb 24
Image Transformations(2D)
Feb 26
Mar 03
Mar 05
Midterm Exam
Project 2 Due on March 6
Mar 10
Spring Break; No Class.
Mar 12
Spring Break; No Class.
Mar 17
Multi-view Geometry(3D)
Mar 19
Mar 24
Mar 26
Mar 31
Project 3 Due on April 1
Video Analysis
Apr 02
Apr 07
Apr 09
Apr 14
Project 4 Due on April 15
Apr 16
No Class.
Apr 21
Apr 23
Temporal Bayesian Inference
Apr 28
Kalman Filter & Extended Kalman Filter
Apr 30
Project 5 Due on April 30