EECS 504
Foundations of
Computer Vision
Fall 2016

Full Teaching List

EECS 504: Foundations of Computer Vision

Instructor: Jason Corso (jjcorso)
GSI : Parker Koch (pakoch)
Lecture Time/Place:MW 1200-1330 in 1500 EECS
Discussion Time/Place:W 1900-2000 in Cooley G906
Discussion is optional
Prof. Office Hours: T 1350-1450 and R 1100-1200 by appt.
GSI Office Hours (in EECS 2420): TR 1430-1600
Syllabus: /~jjcorso/t/504F16/files/504F16_syllabus.pdf
Current Students: This course uses the Canvas LMS to disseminate regularly updated course material, house discussions, and other important information.

Course Description

Computer Vision seeks to extract useful information from images of various types. This course covers the foundations of computer vision. It emphasizes computer vision as a search for visual invariants and computer vision as mathematical modeling. Foundational representations of images and image content will be discussed. Cross-cutting problems of reduction (e.g., feature extraction, segmentation), estimation (e.g., post estimation, camera calibration), and matching (e.g., image stitching, stereo reconstruction) will be concretely defined and elaborated through many real examples from modern computer vision.

The course is designed for graduate students and will prepare them for future work in computer vision. The students will develop a strong understanding of formulating and solving problems in computer vision. The students will develop a rich, capable computer vision system over the course of the semester through homework assignments.

Rough Topic Outline

  • Representation and Computer Vision as Optimization
  • Visual Invariance (photometric, geometric (shift, rotation, affine, scale), projective, structural, deformation, rate)
  • Reduction Problems (feature extraction, segmentation and grouping, etc.)
  • Estimation Problems (line and curve fitting, pose estimation, camera calibration, bundle adjustment, etc.)
  • Matching Problems (stereo correspondence, image stitching, image registration, etc.)

Other Pieces of Information

The course is designed for graduate students and will prepare them for future work in computer vision.

No prior computer vision course is assumed.

The course will cater broadly to students across the College of Engineering, LSA (Stats, Math) and School of Information.

ECE Program Requirement Information

This course satisfies the ECE M.S. Computer Vision major requirement of a graduate computer vision course.

CSE Program Requirement Information

This course satisfies the CSE M.S. degree requirement of "at least 15 credit hours of CSE technical courses at the 500 level or above".

This course counts as a depth course for the CSE PhD requirements.


last updated: Wed Dec 11 11:06:11 2019; copyright jcorso
Please report broken links to Prof. Corso jjcorso@eecs.umich.edu .