Computer Vision

CSE 576, Spring 2013

The goal of computer vision is to compute properties of the three-dimensional world from digital images. Problems in this field include identifying the 3D shape of an environment, determining how things are moving, and recognizing familiar people and objects, all through analysis of images and video. This course provides an introduction to computer vision, including such topics as feature detection, image segmentation, motion estimation, image mosaics, 3D shape reconstruction, and object recognition.

Course Staff

Instructor: Ira Kemelmacher
Office: CSE 650
Office hours: Wednesdays, 3pm-4pm
TA: Ankit Gupta
Office hours: Thursdays, 2pm-3pm (CSE 220)


  • Data structures
  • A good working knowledge of C and C++ programming
  • Linear algebra
  • Vector calculus
No prior knowledge of computer vision is assumed.


  • Required: Richard Szeliski, Computer Vision: Algorithms and Applications (Online edition).
  • Optional: Forsyth & Ponce, Computer Vision: A Modern Approach.
  • Optional: Nalwa, A Guided Tour of Computer Vision.


  • Email List: Please subscribe to the course email list here.
  • We have a discussion board for the course. Please feel free to post any doubts, or answer your classmates' questions. The course staff will also be active on the forum, answering any questions.
  • Computer Accounts: if you don't have a CSE account and want one for this class, click here.
  • Grading: The grade is based on four programming projects.


Class schedule

  • Time: 1:30pm - 2:50pm (Mon and Wed)
  • Place: MGH 234, Mary Gates Hall, UW.

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