Princeton University Computer Science Department

Computer Science 429 Computer Vision Fei-Fei Li

Fall 2008

Course Summary

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; shape reconstruction from stereo, motion, texture, and shading. 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 C, C++, and/or 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.

Administrative Information

Lectures: TTH 1500-1620, Room: TBD

Professor: Fei-Fei Li - CS Building - 258- feifeili@cs.princeton.edu

Undergraduate Coordinator: Donna O'Leary - 410 CS Building - 258-1746 doleary@cs.princeton.edu

Teaching Assistants: TBA