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CSE 527: INTRODUCTION
TO
COMPUTER
VISION
Course Description -- Spring 2008
(pdf file)
CLASS INFORMATION:
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Lectures:
Tue/Thu 12:50-2:20
Location: Computer Science Bldg. room 2129 |
Instructor:
Prof. M. Alex O. Vasilescu
Office Hours: Thu 3-4pm |
Course Description:
Introduction to basic concepts in
computer vision. Low level image analysis, image formation, edge
detection, segmentation. Image transformations for image synthesis,
methods for 3D scene reconstruction, motion analysis, object
recognition.
Prerequisites:
Linear Algebra, Probability, or consent of the instructor.
Grading:
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Option A |
Option B |
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Problem Sets
(~6) with lab exercises in Matlab.
Problem sets may be discussed, but all written work and
coding must be done individually. |
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30% |
30% |
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Exams:
Two take-home exams. No final exam.
(Take-home exams may not be discussed.)
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40% |
0% |
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Final Project:
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An original
implementation of a new or published idea
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A detailed empirical
evaluation of an existing implementation of one or more
methods
Project proposal not longer than two pages must be submitted
and approved before the end of March. |
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30% |
70% |
Textbooks and Reading material:
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Computer Vision: A
Modern Approach, by David Forsyth and Jean Ponce., Prentice
Hall, 2003.
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Robot Vision, by
Berthold Horn, MIT Press 1986.
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Selected journal
articles
Internet Resources:
Matlab:
University of Colorado Matlab Tutorials
o
A decent collection of
Matlab tutorials, including one focusing on
image processing.
Matlab Image Processing Tutorial
o
A short introduction
to the manipulation of images in Matlab, including an introduction
to principal components analysis via
eigenfaces.
Computer
Vision:
Computer Vision Homepage,
Face Recognition Homepage,
Face Detection Homepage
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