This course provides a comprehensive introduction to computer vision. Major topics include image processing, detection and recognition, geometry-based and physics-based vision and video analysis. Students will learn basic concepts of computer vision as well as hands on experience to solve real-life vision problems.

To get started with the class you need to do just three things:

1. Sign up for the course Piazza.
2. Sign up for an account on this webpage. (The signup code is on Canvas.)
3. Carefully read through the Course Info.

Jan 12 (Mon)	Course Introduction
Jan 14 (Wed)	Image Filtering Assignment 0 out
Jan 19 (Mon)	NO CLASS (MLK Jr Day)
Jan 21 (Wed)	Image Pyramids and Frequency Domain Assignment 0 DUE Assignment 1 out
Jan 26 (Mon)	Hough Transform
Jan 28 (Wed)	Detecting Corners
Feb 2 (Mon)	Feature Detectors and Descriptors
Feb 4 (Wed)	2D Transformations Assignment 1 DUE Assignment 2 out
Feb 9 (Mon)	Image Homographies
Feb 11 (Wed)	Geometric Camera Models
Feb 16 (Mon)	Geometric Camera Models (cont.)
Feb 18 (Wed)	Two-View Geometry Assignment 2 DUE Assignment 3 out
Feb 23 (Mon)	Stereo
Feb 25 (Wed)	Image Classification
Mar 2 (Mon)	NO CLASS (Spring Break)
Mar 4 (Wed)	NO CLASS (Spring Break)
Mar 9 (Mon)	Image Classification (cont.)
Mar 11 (Wed)	Neural Networks Assignment 3 DUE Assignment 4 out
Mar 16 (Mon)	Neural Networks (cont.)
Mar 18 (Wed)	Convolutional Neural Networks
Mar 23 (Mon)	Optical Flow
Mar 25 (Wed)	Alignment and Tracking Assignment 4 DUE Assignment 5 out
Mar 30 (Mon)	Alignment and Tracking (cont.)
Apr 1 (Wed)	Radiometry and Reflectance
Apr 6 (Mon)	Radiometry and Reflectance (cont.)
Apr 8 (Wed)	Photometric Stereo Assignment 5 DUE Assignment 6 out
Apr 13 (Mon)	Digital Photography
Apr 15 (Wed)	Digital Photography (cont.)
Apr 20 (Mon)	Special Topics
Apr 22 (Wed)	Wrap-up
Apr 24 (Fri)	Assignment 6 DUE

(Due Jan 21st)

Programming Assignment 0: Introduction to Python

(Due Feb 4th)

Programming Assignment 1: Image Filtering and Hough Transform

(Due Feb 18th)

Programming Assignment 2: Augmented Reality with Planar Homographies

The lecture notes have been pieced together from many different people and places. Special thanks to colleagues for sharing their slides: David Held, Kris Kitani, Bob Collins, Srinivasa Narashiman, Martial Hebert, Alyosha Efros, Ali Faharadi, Deva Ramanan, Yaser Sheikh, and Todd Zickler. Many thanks also to the following people for making their lecture notes and materials available online: Steve Seitz, Richard Selinsky, Larry Zitnick, Noah Snavely, Lana Lazebnik, Kristen Grauman, Yung-Yu Chuang, Tinne Tuytelaars, Fei-Fei Li, Antonio Torralba, Rob Fergus, David Claus, and Dan Jurafsky.