COS 429 - Computer Vision
|Course home||Outline and Lecture Notes||Assignments|
An introduction to the concepts of 2D and 3D computer vision. Topics include: low-level image processing methods such as filtering and edge detection; segmentation and clustering; optical flow and tracking; recognition; shape reconstruction from stereo, motion, texture, and shading; and recent developments in deep learning. Throughout the course, we also look at aspects of human vision and perception that guide and inspire computer vision techniques.
Prerequisites: Prerequisites for the course are COS 217 and COS 226. The course will require programming in Matlab, as well as some background in data structures and linear algebra. Experience with signal processing, statistics, and/or computer graphics is useful but not necessary.
Grading: There will be four assignments worth 56% of the final grade total, a midterm worth 20% and a final project worth 24%.
Midterm: The midterm will be during class time on Thu, Oct 26. No exceptions or alternate times will be offered.
TTh 3:00-4:20, in Computer Science Building Rm 104
Instructor: Prof. Olga Russakovsky
Guest lecturer: Dr. Andras Ferencz, Mobileye Inc.
TAs: Kyle Genova and Riley Simmons-Edler
Undergrad coordinator: Colleen Kenny-McGinley (ckenny at cs, CS 210)
We will be using piazza for Q&A. Please post your questions there instead of mailing the Professor or TAs, if at all possible.
Professor office hours: Mon 9:30-10:30am in CS 408
TA office hours: We will be holding special office hours on weeks when assignments are due and on the week of the midterm.
Regular TA office hours on the weeks of Sep 18, Sep 25, Oct 9, Nov 6, Nov 20, Nov 27, Dec 11:
Tue 4:30-5:30pm with Kyle in CS 418a
Fri 10:30-11:30am with Riley in CS 418a
Special TA office hours on Oct 4, Oct 18, Oct 25, Nov 15 and Dec 7:
Wed 4:30-6:30pm with both TAs in CS 003