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EECS 4422 Computer Vision
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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.
Course textbook. Richard Szeliski, Computer Vision: Algorithms and Applications (available for free or purchase)
Lectures.
# | TOPIC | SLIDES
![]() ![]() |
BACKGROUND MATERIAL |
---|---|---|---|
0 |
Introduction to computer vision | PDF MOV | Szeliski - Chapter 1 Eero Simoncelli, A Geometric Review of Linear Algebra |
IMAGE
FORMATION |
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1 |
Image formation (part 1) | PDF MOV | Szeliski - Chapter 2
(Sec. 2.1) History of Photography in 5 Minutes (video) |
2 |
Image formation (part 2) | PDF MOV | |
3 |
Image transformations |
PDF MOV | |
4 |
Image
metrology |
PDF MOV | Bringing Pictorial Space to Life
|
IMAGE
FILTERING AND FEATURE EXTRACTION |
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5 |
Image filtering: Smoothing | PDF MOV | Szeliski - Chapter 3 (Secs. 3.1 to 3.2.2) |
6 |
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 |
7 |
Image features | PDF MOV | Szeliski - Chapter 4 (Sec. 4.1) |
MODEL FITTING |
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8 |
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 |
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9 |
Frequency analysis: Theory |
PDF MOV | Szeliski - Chapter 3 (Sec. 3.4) |
10 |
Frequency analysis: Applications |
PDF MOV | Horn - Chapters 6 and 7 |
11 |
Image Pyramids |
PDF MOV | |
MULTIPLE IMAGE ANALYSIS | |||
12 |
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) |
13 | Stereopsis | PDF MOV | Trucco and Verri - Chapter 7 |
14 | Camera Calibration |
PDF MOV | |
15 | 3D structure and motion |
PDF MOV | Trucco and Verri - Chapter 8 (Secs. 8.1 and
8.2) |
16 | Tomasi
and Kanade Factorization Method |
PDF MOV | Tomasi and Kanade, Shape and Motion from Image Streams under Orthography: A Factorization Method |
17 |
Procrustes
analysis |
PDF MOV | |
RECOGNITION | |||
18 |
Machine learning crash course |
PDF MOV |
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.
Python Numpy tutorial
Basic
Linear algebra review
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.