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CSBP441: Applied Computer Vision

Description:Fundamentals of computer vision: Pattern recognition concepts; Low-level (early) visual processing; Color histogram for object recognition and tracking; Optical flow motion vector estimation for video surveillance and sequence processing; Stereo analysis for range to object estimation; Disparity estimation for 3D object reconstruction.
Credit Hours.:3
Text Book: Computer Vision, Linda G. Shapiro and George C. Stockman, Prentice Hall, 2001, ISBN-13: 978-0130307965
Coordinator: Jose Lopez Berengueres
Topics Outline:
  1. Fundamentals of computer vision.
  2. Pattern Recognition.
  3. Low-level visual processing.
  4. Color histogram.
  5. Object recognition and tracking.
  6. Optical flow motion vector estimation for video surveillance and sequence processing.
  7. Stereo analysis for range to object estimation.
  8. Disparity estimation for 3D object reconstruction.
Outcomes:
  1. Explain basic concepts of Computer Vision.
  2. Apply technology components for building and operating machine-vision systems.
  3. Implement computer vision concepts using a programming language.
  4. Integrate computer vision techniques into a medium size system.
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Pre-requisiteCSBP421: Smart Computer Graphics
CSBP301: Artificial Intelligence
Volume of the Course that Contributes to CIT Students Outcomes(SOs)
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a b c d e f g h i j k l m n
6% 8% 8% 6% 0% 6%0% 2% 15% 15% 8% 13% 6% 0%
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