CAP5415 - Computer Vision

Fall 2004
MW 16:30 - 17:45
BHC 129


Instructor

Dr. Alper Yilmaz
Email: yilmaz@cs.ucf.edu
Office hours: Mon, 3:00-4:30pm, Wed, 3:00-4:00pm, (CSB 250) 
Phone: 

Teaching Assistant

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Course Goal

The course is introductory level. It will cover the basic topics of computer vision, and introduce some fundamental approaches for computer vision research. 

  • Imaging Geometry
  • Camera Modeling and Calibration
  • Filtering and Enhancing Images
  • Region Segmentation
  • Color and Texture
  • Line and Curve Detection
  • Shape Analysis
  • Stereopsis
  • Motion and Optical Flow
  • Structure from X
  • Grading Policy

    Biweeky Assignments: 20%
    Programming Assignments: 30%
    Mid-Term Exam: 20%
    Final Exam: 30%

    Prerequisites

    A good background in calculus, geometry, linear algebra, programming in MATLAB or C.

    The University Golden Rules will be observed in this class. Copying or Plagiarism is violation of the Golden Rules.


    Reference Text:

  • Course Text Book: Emanuele Trucco, Alessandro Verri, "Introductory Techniques for 3-D Computer Vision", Prentice Hall, 1998. 
  • Lecture Notes: Mubarak Shah, "Fundamentals of Computer Vision". 

  • Lectures

    Lecture 1 (August 23, 2004) ppt file

  • Introduction and brief history
  • Course Overview
  • Lecture 2 (August 25, 2004) ppt file

  • Imaging geometry
  • Lecture 3 (August 30, 2004) ppt file

  • Imaging geometry continued
  • Estimating camera parameters
  • Lecture 4 (September 1, 2004) ppt file

  • Images
  • Noise
  • Derivative, convolution etc.
  • Lecture 5 (September 8, 2004) ppt file

  • Filtering
  • Edge Detection
  • Lecture 6 (September 13, 2004) ppt file

  • Marr Hildreth edge detector
  • Canny edge detector
  • Lecture 7 (September 15, 2004) ppt file

  • Region Segmentation
  • Lecture 8 (September 19, 2004) ppt file

  • Region Segmentation continued
  • Lecture 9 (September 22, 2004) ppt file

  • Region Properties
  • Lecture 10 (September 29, 2004) ppt file

  • Gaussian pyramid
  • Laplacian pyramid
  • Lecture 11 (October 4, 2004) ppt file

  • Review
  • MidTerm (October 6, 2004)

    Lecture 12 (October 11, 2004) ppt file

  • Line Fitting
  • Lecture 13 (October 13, 2004) ppt file

  • Circle Fitting
  • Generalized Hough transform
  • Medial axis transform
  • Movarec's interest operator
  • Harris corner detector
  • Lecture 14 (October 18, 2004) ppt file

  • Optical flow
  • Horn & Schunck
  • Schunck
  • Lucas & Kanade
  • Lecture 15 (October 20, 2004) ppt file

  • Global Motion
  • Anandan's method
  • Lecture 16 (October 25, 2004) ppt file

  • Global Motion
  • Token and Patch based optical flow
  • Lecture 17 (October 27, 2004) ppt file

  • Shape From Motion (SFM)
  • Lecture 18 (November 1, 2004) ppt file

  • Stereopsis
  • Lecture 19 (November 8, 2004) ppt file

  • Stereopsis
  • Epipolar geometry
  • Lecture 20 (November 10, 2004) ppt file

  • Estimating fundamental matrix
  • Normalized Cuts for image segmentation
  • Lecture 21 (November 15, 2004) ppt file

  • Discussion on 2nd programming project
  • Lecture 22 (November 17, 2004) ppt file

  • Midterm 2 overview part 1
  • Lecture 23 (November 22, 2004) ppt file

  • Midterm 2 overview part 2
  • Mid Term (November 24, 2004) ppt file



    Programming Assignments

  • Implement canny and Marr-Hilredth edge detectors
  • Implement Lucas Kanade optical flow using Gaussian pyramids

  • Sample images:

  • calendar sequence
  • running sequence
  • flower garden sequence

  • Source Code:

    cimage.cpp cimage.h


    Leading Journals and Conferences in Computer Vision

  • International Journal of Computer Vision (IJCV)
  • Pattern Analysis and Machine Intelligence (PAMI)
  • IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)
  • International Conference on Computer Vision (ICCV)

  • Some other Links

  • UCF Computer Vision Lab Home Page
  • Computer Vision Home Page