Computer Vision Models: Applications of Density Models

Wednesday, June 16, 2010

Applications of Density Models

I've been working for the last couple of days making figures showing applications for density modeling in Chapter 6. I'm going to give examples of skin detection, background subtraction and face recognition.

I've also corrected a bunch of mistakes in Chapter 5 that were spotted by my PhD student Yun Fu.

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Contents

Part I: Probability

1. Introduction to probability
2. Probability distributions
3. Fitting probability distributions
4. The multivariate normal

Part II: Machine learning for machine vision

5. Learning and inference
6. Complex probability densities
7. Regression models for vision
8. Classification models for vision

Part III: Connecting local models

9. Graphical models
10. Directed models for images
11. Markov random fields

Part IV: Preprocessing

12. Preprocessing methods

Part V: Models for geometry

13. Pinhole camera model
14. Transformation models
15. Multiple cameras

Part VI: Computer vision models

16. Models for shape
17. Models for identity and style
18. Temporal models
19. Models for visual words

Part VI Appendices

A. Optimization

B. Image preprocessing and feature extraction

C. Linear algebra

D. Algorithms