introduction to computer vision dr. chang shu comp 4900c winter 2008
TRANSCRIPT
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Introduction to Computer Vision
Dr. Chang Shu
COMP 4900CWinter 2008
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Instructors:
Chang Shu ([email protected])
Gerhard Roth ([email protected])
Institute for Information Technology
National Research Council
TA: Stefanie Wuhrer
Course website: www.scs.carleton.ca/~c_shu/Courses/comp4900d/
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What is Computer Vision?
The goal of computer vision is to develop algorithms that allow computer to “see”.
Also called• Image Understanding• Image Analysis• Machine Vision
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General visual perception is hard
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Digital Image
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A brief history of computer vision
• 1960s - started as a student summer project at MIT.
• 1970s and 80s – part of AI – understanding human vision and emulating human perception.
• 1990s – depart from AI , geometric approach.• Today – various mathematical methods
(statistics, differential equations, optimization), applications (security, robotics, graphics).
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What is Computer Vision?
Trucco & Verri:
Computing properties of the 3-D world from one or more digital images.
Properties: mainly physical (geometric, dynamic, etc.)
My favorite:
Computer vision is inverse optics.
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Related fields• Image Processing• Pattern Recognition• Photogrammetry• Computer graphics
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Our Time
It is a good time to do computer vision now, because:
• Powerful computers• Inexpensive cameras• Algorithm improvements• Understanding of vision systems
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Applications: 3D Reconstruction
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Augmented Reality
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Panoramic Mosaics
+ + … + =
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Applications: Recognition
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ESC Entertainment, XYZRGB, NRC
Applications: Special Effects
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Andy Serkis, Gollum, Lord of the Rings
Applications: Special Effects
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Applications: Medical Imaging
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Autonomous Vehicle
Flakey, SRI
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Applications: Robotics
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Applications: Surveillance
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Mathematical tools
• Linear algebra• Vector calculus• Euclidean geometry• Projective geometry• Differential geometry• Differential equations• Numerical analysis• Probability and statistics
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Programming tools
• OpenCV – an open source library for computer vision.
• Ch – a C interpretation environment.
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Course OrganizationTextbook: Introductory Techniques for 3-D Computer
Vision, by Trucco and Verri
Two parts:
Part I (Chang Shu) – Introduction, Review of linear algebra, Image formation, Image processing, Edge detection, Corner detection,
Line fitting, Ellipse finding.
Part II (Gerhard Roth) – Camera calibration, Stereo, Recognition, Augmented reality.
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Evaluation
Four assignments (50%)
Two mid-terms (50%)
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Programming tools
• OpenCV• A library of routines useful for computer vision• Open Source system widely used around the world• Contains many examples and demo programs• Requires VC++ or Ch interpreter to use
• VC++ or Ch• Assignments normally written in C++ or C• The easiest way to use the OpenCV library is with
– VC++ 6.0 (examples are on the CD)
– The .net version of VC++ should also work
– Another option is Ch, a C interpreter (also on the CD)
– No advantages over C++ except ease of use (but slower)
• Course CD has OpenCV and Ch interpreter