CS 410/510: Foundations of Computer Vision

Instructor: Feng Liu

TA: Zhan Li
Office: Zoom   Office: https://pdx.zoom.us/j/84063267395
Office Hours: email for an appointment Office Hours: TR 14:30-15:30
Email: fliu@pdx.edu Email: lizhan@pdx.edu

  • Project presentation schedule (You need to login using your pdx.edu account)
  • Homework 3 is available. Due on 4:30 pm 03/10/2022
  • Project is announced. Proposal due 4:30 pm, February 8.
  • Homework 2 is available. Due on 4:30 pm 02/08/2022
  • Homework 1 is available. Due on 4:30 pm 01/20/2022
  • Tutorials on installing Python with OpenCV is available. You need to log in using your pdx.edu account.

This new course will provide an introduction to computer vision. It will cover algorithms in computer vision and image/video processing. It will focus on the development of visual computing applications using off-the-shelf computer vision libraries, such as OpenCV.
General Course Information
  • Pre-Requisites: CS 202 or its equivalence
  • Schedule: TR 16:40-18:30, Zoom link, sent to your pdx.edu account
  • Syllabus
  • Grading policy: Homework (65%) + Project (35%)
    a. No late homework or project assignment will be accepted for this class.
    b. Online source code cannot be used for homework assignments and project without an explicit permission.
    c. This class enforces the PSU Student Conduct Code.
  • Mailing lists: we will use Google Chat for this class.

We do not require any textbooks for this class. But the following two books will be very helpful.

Computer Vision: Algorithms and Applications, by R. Szeliski

This book is available online. Please download its latest version.

Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library,
by Adrian Kaehler and Gary Bradski.

This book focuses on the C++ version of OpenCV while this course uses the Python one. But this book provides not only a good reference to the OpenCV library, but also very good descriptions of a vast amount of vision algorithms.

OpenCV documentation is your friend!

Acknowledgement: Many of the lecture notes were modified or taken from materials for similar classes taught at other universities by Professor Lazebnik, Svetlana, Yung-Yu Chuang, Fr¨¦do Durand,  Alexei Efros, Chuck Dyer, Marc Levoy, Steve Seitz, Li Zhang, and Dr. Stephen Chenney and Richard Szeliski. Without their generous help, this class could not have been developed.
Date Topic Notes *Readings
W10: 03/10 Project presentation  Schedule  
W10: 03/08 Project presentation   
W9: 03/03 Face Detection Notes OpenCV Book: Chapter 20, 21
W9: 03/01 Machine learning approach to object recognition Notes
W8: 02/24 Object recognition: overview Notes Szeliski Book: Chapter 6
W8: 02/22 Structure from motion Notes OpenCV Book: Chapter 19
W7: 02/17 Epipolar geometry Notes Szeliski Book: Chapter 11.3.1, OpenCV Book: Chapter 19
W7: 02/15   Homework 3 Slides Required reading (before class):
Section 3.3

Simon Baker, Daniel Scharstein, J. P. Lewis, Stefan Roth, Michael J. Black, and Richard Szeliski. A Database and Evaluation Methodology for Optical Flow, International Journal of Computer Vision, 92(1):1-31, March 2011.
W6: 02/10 Camera calibration Notes OpenCV Book: Chapter 18
W6: 02/08      
W5: 02/03 Motion estimation Notes OpenCV Book: Chapter 16, 17
W5: 02/01 Image warping and morphing Notes Szeliski Book: Chapter 3.6
W4: 01/27 Image alignment Notes Szeliski Book: Chapter 8.1
W4: 01/25 Hough transform Notes Szeliski Book: Chapter 7.4.2
W3: 01/20 Matching and Fitting Notes
W3: 01/18 Scale-invariant feature detection Notes OpenCV Book: Chapter 16
or Szeliski Book: Chapter 7.1
W2: 01/13 Corner detection Notes
W2: 01/11 Edge detection Notes OpenCV Book: Chapter 10, 12
or Szeliski Book: Chapter 7.2
W1: 01/06 Filter Notes OpenCV Book: Chapter 10
Szeliski Book: Chapter 3.1, 3.2
W1: 01/04 Course overview
Image representation
Notes OpenCV Book: Chapter 8
* You might need to be on the PSU network or have an ACM/IEEE account to download some of papers.

Homework Assignments
Programming Resources
1. OpenCV
2. OpenCV-Python Installation. You need to log in using your pdx.edu account.