Description from Joseph Redmon's Ancient Secrets of Computer Vision
This class is a general introduction to computer vision. It covers standard techniques in image processing like filtering, edge detection, stereo, flow, etc. (old-school vision), as well as newer, machine-learning based computer vision. It was originally offered in the spring of 2018 at the University of Washington.
Instructors
Joseph Redmon
Ali Farhadi
Slides are a mishmash of lots of other people's work. Special thanks to: Rob Fergus, Linda Shapiro, Harvey Rhody, Rick Szeliski, Ali Farhadi, Robert Collins. Lectures 8 and 9 on Flow, 3d, and stereo are given by Connor Schenck.
All of the slides, videos, and homeworks are free to use, modify, redistribute as you like without permission. Just make your own copy of the slides on Google Docs, don't ask to modify mine!
The class has 6 homeworks where you will build out a computer vision library in C. We cover basic image manipulations, filtering, features, stitching, optical flow, machine learning, and convolutional neural networks.