Topics list and reading list for depth exam in Computer Graphics, Multimedia and Computer Vision

Depth Exam
Computer Graphics, Multimedia and Computer Vision


The depth exam in areas related to Computer Graphics, Multimedia and
Computer Vision, requires mastery of the material for the breadth exam in 
Computer Graphics and Image Analysis, as well as mastery of the 
supplemental material shown below.  The committee recommends preparation 
for the exam by taking courses recommended for the breadth exam 
(CS535 - Computer Graphics and CS635 - Image Processing) as well as 
advanced courses related to the area in which the depth will be taken.

Topics are covered in the material shown below on the exam reading list,
which are in addition to the reading list required for the Breadth exam
in Computer Graphics and Image Analysis.

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Topics list (Computer Graphics):

1. Topics covered in the breadth exam
2. Shadow generation algorithms
3. Visualization Techniques
4. Advanced Raster Graphics Architecture
5. Advanced Geometric and Raster Algorithms
6. Advanced Modeling Techniques 
7. Subdivision surfaces and their applications
8. Radiosity

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Reading List (Computer Graphics):

[1].  Foley, van Dam, Feiner, and Hughes,
      Computer Graphics: Principles and Practice, 2nd edition in C
	 (Publisher: Addison-Wesley)
     ISBN no: 0-201-84840-6

[2]. Woo, A., Poulin, P., and Fournier, A., A Survey of Shadow Algorithms,
     IEEE Computer Graphics & Applications 10 (November, 1990), 13-32.

[3]. Nielson, G.M., Hagen, H. and Muller, H.,
     Scientific Visualization
	 (Publisher: IEEE Computer Scociety)
	 ISBN no: 0-8186-7777-5

[4]. T. DeRose, M. Kass, and T. Truong,
     Subdivision surfaces in Character Animation,
     Computer Graphics 32 (July, 1998), 85-94.

[5]. Cohen, Chen, Wallace and Greenberg,
     A Progressive Refinement Approach to Fast Radiosity Image Generation,
     Computer Graphics 22,4 (August 1988), 137-145.

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Topics List (Multimedia and Computer Vision):

1. Image Formation, Color, Human/Primate Vision
2. Overview of Feature Extraction Methods
3. Image-Alignment and Pictorial Descriptions
4. Object, Scene, and World Representation
5. Pose Estimation and Recovery
6. Classification Techniques
7. Model Fitting, Regression
8. Learning and Vision
9. Signal Processing and Image Enhancement
10. Image and Video Representation/Compression 
11. Object Recognition, Perceptual Grouping
12. Tracking and Recognition
13. Stereo Vision
14. Camera Calibration
15. Three-Dimensional Reconstruction
16. Model Representation 
17. Spatial Media and Geospatial Model Acquisition
18. Epipolar Geometry
19. Projective Geometry

Reading List (Multimedia and Computer Vision):

[1].  Gonzales, E. Woods,  Digital Image Processing, Addison-Wesley, 1993.

[2].  Trucco, A. Verri, Introductory Techniques for 3D Computer Vision, 
      Chapters 1-4, Prentice-Hall, 1998.

[3].  Bovik, Handbook of Image and Video Processing, Chapter 2. Academic 
      Press, 2000.

[4].  MPEG-2 Standard (web resource).

[5].  H. Gilbert,  Data and Image Compression : Tools and Techniques, 
      John Wiley & Sons, Inc, 1996.

[6].  B. Horn, Robot Vision, McGraw-Hill, 1985.

[7].  O. Faugeras, Three-Dimensional Computer Vision: A Geometric 
      Viewpoint , MIT Press, 1993.
 
[8].  Jaynes, Suplemental Notes "The Projective Plane", available at 
      www.dcs.uky.edu/~jaynes/cs636/

[9].  H. Anton, Elementary Linear Algebra, Wiley, 1984.

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