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EECS 4422/5323 Computer Vision
Fall 2021

with Prof. Kosta Derpanis


Course description. This course introduces the fundamental concepts of vision with emphasis on computer science and engineering.  In particular, the course covers the image formation process, image representation, feature extraction, stereopsis, motion analysis, 3D parameter estimation and applications.

Contact information. kosta [at] eecs.yorku [dot] ca

Homepage
. www.eecs.yorku.ca/~kosta

Course textbook. Richard Szeliski, Computer Vision: Algorithms and Applications (available for free or purchase)

Syllabus.  Available in the eLearn course shell

Announcements and assignment. Available in the Brightspace course shell

Teaching assistants. Matthew Kowal (m2kowal [at] ryerson dot ca)

Lectures. Below is the tentative schedule of topics (links to slides will be made available after each lecture)

# DATE TOPIC SLIDES
 quicktime
BACKGROUND MATERIAL
0
Sept. 9
Introduction to computer vision PDF MOV Szeliski - Chapter 1

Eero Simoncelli, A Geometric Review of Linear Algebra
IMAGE FORMATION
1
Sept. 13
Camera optics (part 1) PDF MOV Szeliski - Chapter 2 (Sec. 2.1)

History of Photography in 5 Minutes (video)
2
Sept. 15
Camera optics (part 2) PDF MOV
3
Sept. 22
Image transformations
PDF MOV
IMAGE FILTERING AND FEATURE EXTRACTION
4 Sept. 22 Image filtering (smoothing) PDF MOV Szeliski - Chapter 3 (Secs. 3.1 to 3.2.2)
5
Sept. 29
-
Oct. 4
Image filtering (edge detection) PDF MOV Szeliski - Chapter 4 (Sec. 4.2)

Pedro Felzenszwalb, Edge Detection

Avidan and Shamir, Seam Carving for Content-Aware Image Resizing
6
Oct. 6 - Oct. 18 Image features PDF MOV Szeliski - Chapter 4 (Sec. 4.1)
MODEL FITTING
7

Model fitting PDF MOV Szeliski - Chapters 4 (Sec. 4.3.2) and 6 (Secs. 6.1.1, 6.1.2 and 6.1.4)

Ballard and Brown, Hough transform
FREQUENCY ANALYSIS
8

Frequency analysis (part 1) PDF MOV Szeliski - Chapter 3  (Sec. 3.4)
9

Frequency analysis (part 2) PDF MOV Horn - Chapters 6 and 7
RECOGNITION
10

Machine learning crash course
PDF MOV
MULTIPLE IMAGE ANALYSIS
11

Motion analysis PDF MOV Trucco and Verri - Chapter 8 (Secs. 8.3 and 8.4)

Fleet and Weiss, Optical Flow Estimation
(Secs. 1 and 2)

12
Stereopsis PDF MOV Trucco and Verri - Chapter 7
13

3D structure and motion
PDF MOV Trucco and Verri - Chapter 8 (Secs. 8.1 and 8.2)

Reference textbooks.
     Gilbert Strang, Linear Algebra and Its Applications (video lectures)
     Berthold Horn, Robot Vision, MIT Press.
     Emanuele Trucco and Alessandro Verri, Introductory Techniques for 3-D Computer Vision, Prentice Hall.

Useful links.
     MATLAB install for York students
    
MATLAB tutorial
    
MATLAB primer
     Basic Linear algebra review
     
Linear Algebra review and MATLAB tutorial

     Linear algebra review and reference

Acknowledgements. While a great effort has been made to assemble an original set of lecture slides, the essence of the presentation of many of the slides rely significantly on slides prepared by the following instructors: Richard Wildes, Kostas Daniilidis, James Hays, Derek Hoiem, Aaron Bobick, David Lowe, Kristen Grauman, Robert Collins, Svetlana Lazebnik, Steve Seitz, William Freeman, Robert Pless, Andrej Karpathy and Alyosha Efros.