‎"Behind every stack of books there is a flood of knowledge."

Computer Vision EGGN 512 / CSCI 512


Course description

Computer vision is the process of using computers to acquire images, transform images, and extract symbolic descriptions from images.  The automatic classification of blood cells in medical images and the robotic control of an unmanned lunar rover are examples of computer vision applications.  This course provides an overview of this field, starting with image formation and low level image processing.  We then go into detail on the theory and techniques for extracting features from images, measuring shape and location, and recognizing objects.  Design ability and hands-on projects will be emphasized, using image processing software and hardware systems.  The intended audience for the course is graduate students in science and engineering, although qualified undergraduates are welcome.  3 hours lecture.


Associate Professor William Hoff
Room BB314H (Brown Hall) 
Phone: (303) 273-3761 
Home page: 
Office hours: M 2-3, M 4-5, W 2-3 (or by appointment) 

Useful Links

Semester:  Spring 2013

Videos are stored on YouTube.

  • You can access them directly by using the links below.
  • Videos are named “EGGN 512 – Lecture #-part# – <description>”.
  Notes Lecture slides and videos Reading (book) Other material
  • (L1) Introduction to Computer Vision (slides)
Ch 1
  • Review of linear algebra by Gonzalez and Woods (slides)
  • Matlab introduction by Gonzalez and Woods (pdf)
  • Matlab image proc toolbox (slides)
2.1.2-2.1.4, 2.2.3,
2.3 (first few pages)
  • Assign HW2
  • Check out cameras from H. Tran
2.1.5, 3.1-3.3
  • Reading & writing movies in Matlab (slides)
2.1.2, 9.1.3, A.2
4.1, 4.2
4.3.2, 8.1
  • Hough transform in OpenCV (slides)
6.1, 6.2
6.2.1, 6.3.2, 6.3.3, A.1.1
  • Exam
  • Spring break
6.3, 7.1
7.2, 7.4
  • (L28) Model based object recognition (slides)
  • (L29) Motion segmentation (slides, video pt1)
  • (L30) Deformable models (slides, video pt1pt2)
14.3.1, 5.1



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