ECE 549
Computer Vision

Displaying course information from Spring 2014.

Section Type Times Days Location Instructor
ON2 ONL -     Svetlana Lazebnik
R LCD 1100 - 1215 T R   0216 Siebel Center for Comp Sci  Svetlana Lazebnik
Official Description Information processing approaches to computer vision, algorithms, and architectures for artificial intelligence and robotics systems capable of vision: inference of three-dimensional properties of a scene from its images, such as distance, orientation, motion, size and shape, acquisition, and representation of spatial information for navigation and manipulation in robotics. Course Information: Same as CS 543. Prerequisite: ECE 448 or CS 225.
Subject Area Robotics, Vision, and Artificial Intelligence
Course Prerequisites Credit in ECE 448 or CS 225
Course Directors Narendra Ahuja
Detailed Description and Outline


  • Image formation: imaging techniques - monocular, binocular; range, brightness, color; digital images
  • Early vision: reflection and brightness; edge detection; human stereo vision, range from stereo images; surface orientation from shading; motion perception in humans; motion estimation from optical flow and motion stereo; motion from optical flow; human texture perception and surface shape from texture gradient; surface shape from contours; active vision
  • Segmentation: multiresolution and multiscale image representations; segmentation; texture models, recognition and discrimination, texture based segmentation; segmentation; texture models, recognition and discrimination, texture based segmentation; segmentation from motion
  • Representation and robotics: image boundary and region representation, shape description; three-dimensional surface representation, object and viewer-centered representations; dynamic representation; navigation
  • Matching and recognition: three-dimensional model generation; object recognition; relaxation processes
  • Computer architectures for vision: model of computer vision; planar array and hierarchial multiprocessor architectures for image analysis and processing

Same as CS 543.


Forsyth and Ponce, Computer Vision, Prentice Hall, 2003.

Collateral Reading:
B. Horn, Robot Vision, McGraw-Hill.

Last updated: 2/13/2013