CS485/CS780 - Computer Vision - Fall'2001

• This course introduces computational models of computer vision and their implementation on computers.  Topics include early vision (camera models, image formation, image features, etc.), mid-level vision (3D vision, motion, shape from X, etc.), and high-level vision (recognition and location).

• E. Trucco and A. Verri, Introductory Techniques for 3D Computer Vision, Prentice Hall, 1998.
• D. Marr, Vision: A Computational Investigation into the Human Representation and Processing of Visual Information, Freeman, San Francisco, 1982.
• Selected papers.

• Early Vision (camera models, image formation, image features)
• image formation - intensity images, digital images
• camera models, intrinsic and extrinsic camera parameters
• image denoising - noise filtering
• image features - edge detection (Canny), corner detection, line & curve detection (Hough transformation), ellipse detection, deformable contours (snakes)
• perceptual organization

• Mid-level Vision (3D vision, motion, shape from X)
• Camera calibration - determining the value of the intrinsic and extrinsic camera parameters
• 3D vision - stereo vision (correspondence & reconstruction)
• motion analysis - motion field, optical flow, tracking (Kalman filter, Condensation), structure from motion
• shape from shading
• shape from texture

• High-level Vision (recognition and location)

• Typical Applications
• Biometrics (example, face recognition)
• Evolutionary Computation in Computer Vision
• Neural Computation in Computer Vision
• Machine learning  in Computer Vision

• Projects (topics are related to our course Contents)
• Class presentation (10-15 min. + 5 min. Q&A)
• Term paper (~ 10 pages)
• Class attendance

Miscellanea

• The Computer Vision Homepage
• CVonline: The Evolving, Distributed, Non-Proprietary, On-Line Compendium of Computer Vision
• Vision Science: An Internet Resource for Research in Human and Animal Vision
• Computer Vision Online Publications
• Sussex Computer Vision Teach Files
• The Face Recognition Home Page
• Face Detection Home Page
• MATLAB
• Matlab Primer (Third Edition, By Kermit Sigmon - pdf file)
• Matlab Getting Started (copyright Mathworks - pdf file)
• Matlab Image Processing Toolbox User's Guide (copyright Mathworks - pdf file)
• Example images for project # 1
• image1 (binary file, image resolution 256 x 384)
• image2 (gif image)
• image3 (gif image)
• Training and testing data for project # 2
• TrainingData.tar (binary files, image resolution 128 x 128)
• TestingData.tar (binary files, image resolution 128 x 128)
• Video sequence for project # 3
• seq.tar (20 binary files, image resolution 200 x 200)