Computational Vision

CSCI-4270

The goal of this course is to introduce students to the problems, challenges, and applications of computer vision from a computational perspective. Topics include camera modeling and image formation, feature extraction, object and face recognition, image mosaic construction, stereo and three-dimensional imaging, motion, and tracking. Machine learning methods, including deep convolutional neural networks, will be studied and applied throughout the course.

4 credits
Cross-listed with:

Past Term Data

Offered
Not Offered
Offered as Cross-Listing Only
No Term Data
Spring Summer Fall
(Session 1) (Session 2)
2023
2022
Computational Vision (4c)
  • Charles V Stewart
Seats Taken: 60/70
2021
Computational Vision (4c)
  • Charles V Stewart
Seats Taken: 43/100
2020
2019
Computational Vision (4c)
  • Charles V Stewart
Seats Taken: 56/66
2018
Computational Vision (4c)
  • Charles V Stewart
Seats Taken: 65/66
2017
Computational Vision (4c)
  • Charles V Stewart
Seats Taken: 28/40
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007