The table below outlines a tentative schedule for this course over a 13-week term. In conjunction to the lectures there will be a 2-hour weekly lab session intended to give practical demonstration of the computer vision principles presented in the lectures and to provide experience in using OpenCV for the development of computer vision components and systems.

Ackowledgements: The slides are a combination of multiple resources and materials generously made publicly available by J. Hays, S. Lazebnik, D. Forsyth, J. Ponce, J. Koenderink, S. Seitz, R. Szeliski, B. Freeman, M. Pollefeys, D. Lowe, K. Grauman, A. Efros, F. Durand, L. Fei-Fei, A. Torralba, R. Fergus. In particular the material is heavily based on Professors S. Lazebnik's and J. Hays' slides.

2016 Winter Semester
Date Topics Chapters Slides Comments
1 > Syllabus
Introduction to Computer Vision
Szeliski Ch. 1, 3.2, Forsyth/Ponce Ch. 4 pdf
Assignment 1 out
2 > Image formation/processing
(edge detection, image sampling)
Szeliski Ch. 3.2, 3.5, 4.2 pdf
Cipolla & Gee on edge detection
3 > Image formation/processing
(feature detection and matching, cameras)
Szeliski Ch. 4, 2 pdf
Assignment 1 due
Assignment 2 out
tutorial MOPS technical report
4 > Review & Demos, Mosaics Szeliski Ch. 9 pdf
Szeliski, Shum 97 paper
5 > Multiple views and motion (stereo, epipolar geometry and structure from motion) Szeliski Ch. 7, 11 pdf
Assignment 2 due
6 > Assignment 1 & 2 solutions, Midterm exam In-class demo
7 > Multiple views and motion (multiview stereo, feature tracking, optical flow) Szeliski Ch. 11.6, Ch. 8.4 pdf
Assignment 3 out
8 > Recognition overview and bag of features Szeliski Ch. 14 pdf
9 > Large-scale instance recognition
Photometric Stereo
Szeliski Ch.14.3.2, Ch. 12 pdf
Assignment 3 due
Project assigned
10 > Sliding Window Face Detection with Viola-Jones
Szeliski Ch.14.1, 14.2 pdf
12 > 3D Reconstruction
Midterm & Assignment 3 solutions
Szeliski Ch. 12.2 pdf Project due
13 > Quiz