EECS 4070

Computer Vision


Syllabus
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Last Modified:
May 21 16:37

Course Description


In this course we will cover a rather wide variety of topics and the student will have a chance to study a particular topic in depth by doing a project. The topics we will cover are:
  • Introduction.
  • Camera Geometry, Lighting, Image Formation.
  • Color
  • Linear filters
  • Image Features and Edge Detection
  • Stereo
  • Structure from Motion
  • Segmentation, Grouping and Model Fitting.
  • Visual Motion and Optical Flow.
  • Matching.
  • Recognition

Lecture Hours

Wednesday, 3:00pm on zoom.

Programming Assignments

Two lab assignments (10% each) and a project that includes a marked proposal, a midpoint progress report, a short oral presentation, a report and a demo in the lab (10+10+10+10+10%). You will use your own equipment and software for the assignments nad the project. The lab assignments, proposal and project will be demoed to the instructor and the project presented during the last lecture.

Tests

There will be a midterm worth 10% and a final worth 20%. The final will cover all the material in the course.

Text

The text is "Computer Vision: A Modern Approach" by Forsyth and Ponce (2nd Edition). The book will be complemented by notes by the instructor.

Other Reading

To refresh your Linear Algebra: Linear Algebra and Its Applications by Gilbert Strang, Brooks Cole; 4th edition (July 19, 2005), ISBN: 0030105676. The textbook also provides a good summary of related topics in math in the appendix.

Last Modified: Sep 9 2016