CPS 843/CP 8307 Introduction to Computer Vision

Winter 2014, Friday 3:00 - 6:00pm, SHE 651.
Instructor: 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.

Prerequisites

This course requires programming experience as well as linear algebra, basic calculus, and basic probability.  The following courses are prerequisites (or equivalent courses at other institutions):

Textbook

Reference Textbooks

Grading

The final grade for is based on the following components:
(It is strongly recommended that all assignments be done in MATLAB, since all starter code will be provided for MATLAB.)

Late Policy

You have three "late days" for this course. Specifically, the first 24 hours after the due date and time counts as 1 day, up to 48 hours is two and 72 for the third late day.  After the three "late days" have been exhausted, an automatic zero will be assigned.

Syllabus (tentative)

Class Date Topic Slides Reading Assignment
Jan. 10th
Introduction to computer vision pdf
mov
Szeliski - Chapter 1

Eero Simoncelli, A Geometric Review of Linear Algebra

Image Formation and Filtering
Jan. 10th Cameras and optics (part 1)
pdf
mov
Szeliski - Chapter 2.1
Jan. 17th
Cameras and optics (part 2)
pdf
mov
Szeliski - Chapter 2.1
A0 released
Jan. 24th Image filtering (smoothing)
pdf
mov
Szeliski - Chapter 3.2 (up to and including 3.2.2)
A0 due
Jan. 31st Image filtering (edge detection)
pdf
mov
Szeliski - Chapter 4.2

Pedro Felzenszwalb, Edge Detection

Features and Fitting
Feb. 7th
Image features (corner detection and SIFT)
pdf
mov
Szeliski - Chapter 4.1
Feb. 14th
Midterm A1 released
Feb. 21st NO CLASS (READING WEEK)
Feb. 28th Model fitting pdf
mov
Szeliski - Chapters 4.3.2,  6.1.1, 6.1.2, 6.1.4 A1 due
A2 released
Frequency Analysis
Mar. 7th Frequency analysis (Part I) pdf
mov
Szeliski - Chapter 3.4

Horn - Chapters 6, 7 (Blackboard: Course readings)

Mar. 14th Frequency analysis (Part II) pdf
mov

A2 due
Multiple Views
Mar. 21st Stereopsis pdf
mov


Mar. 28th Motion analysis pdf
mov
Fleet and Weiss, Optical flow Estimation
Apr. 4th 3D structure and motion
pdf
mov



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, and Alyosha Efros.