CS 682: Computer Visionzduric/cs682/Slides/cs682_Introduction.pdfDr. Zoran Duric (CS Dept. GMU) CS...
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CS 682: Computer Vision Dr. Zoran Duric CS Dept. GMU January 27, 2009 Office: S&T II, Rm. 427 email: [email protected] Office Hours: Tue. 2:00-4:00pm, Thu 1:30-2:30pm or by app. URL: http://www.cs.gmu.edu/∼zduric/ Course: http://www.cs.gmu.edu/∼zduric/cs682.html Dr. Zoran Duric (CS Dept. GMU) CS 682: Computer Vision January 27, 2009 1 / 16
Transcript of CS 682: Computer Visionzduric/cs682/Slides/cs682_Introduction.pdfDr. Zoran Duric (CS Dept. GMU) CS...
CS 682: Computer Vision
Dr. Zoran Duric
CS Dept. GMU
January 27, 2009
Office: S&T II, Rm. 427email: [email protected]
Office Hours: Tue. 2:00-4:00pm, Thu 1:30-2:30pm or by app.URL: http://www.cs.gmu.edu/∼zduric/
Course: http://www.cs.gmu.edu/∼zduric/cs682.html
Dr. Zoran Duric (CS Dept. GMU) CS 682: Computer Vision 1/ 16January 27, 2009 1 / 16
Class Administration
How will the class work?
I will lecture most of the time
There will be discussions, Matlab programming examples
There will be several homework assignments in Matlab
There will be a midterm and a final exam
Students will present their projects
Dr. Zoran Duric (CS Dept. GMU) CS 682: Computer Vision 2/ 16January 27, 2009 2 / 16
Class Administration (cont.)
Grading
Class participation and presentations: 10%
Midterm: 20%
Final: 20%
Homeworks: 30%
Project: 20%
Resources:
Robotics Laboratory has several/many video cameras, R1 470Laboratory for the Study and Simulation of Human Movementhas a other equipment, R1 470/477
Dr. Zoran Duric (CS Dept. GMU) CS 682: Computer Vision 3/ 16January 27, 2009 3 / 16
Class Textbook
Required
M. Sonka, V. Hlavec, and R. Boyle. Image Processing, Analysis, andMachine Vision. Thomson 2008.
Recommended
Matlab with Image Processing Toolbox, can be used on GMUcomputers for free
Svoboda, Kybic, and Hlavec. Image Processing, Analysis, andMachine Vision: A MATLAB Companion. Thomson 2008.
Class notes (will be posted on the class web page).
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Introduction
Chapter 1: Introduction
1.1 Motivation
1.2 Why is computer visiondifficult?
1.3 Image representation andimage analysis tasks
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Introduction Motivation
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Introduction Motivation
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Introduction Motivation
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Introduction Why is computer vision difficult?
Why is computer vision difficult?
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Introduction Why is computer vision difficult?
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Introduction Why is computer vision difficult?
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Introduction Image representation and image analysis tasks
Image representation and image analysis tasks
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Introduction Image representation and image analysis tasks
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Introduction Image representation and image analysis tasks
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Introduction Image representation and image analysis tasks
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Introduction Summary
Summary
Human vision is natural and seems easy; computer mimicry of this isdifficult.We might hope to examine pictures, or sequences of pictures, forquantitative and qualitative analysis.Many standard and advanced AI techniques are relevant.High and low levels of computer vision can be identified.Processing moves from digital manipulation, through pre-processing,segmentation, and recognition to understanding—but these processesmay be simultaneous and co-operative.An understanding of the notions of heuristics, a priori knowledge,syntax, and semantics is necessary.The vision literature is large and growing; books may be specialized,elementary, or advanced.A knowledge of the research literature is necessary to stay up to datewith the topic.Developments in electronic publishing and the Internet are makingaccess to vision simpler.Dr. Zoran Duric (CS Dept. GMU) CS 682: Computer Vision 16/ 16January 27, 2009 16 / 16
