Computer Vision Models: April 2011

Thursday, April 21, 2011

New post

Now completed first draft of the applications, problems, and literature review up to the end of Chapter 11 (Markov Random Fields). Fixed numerous errors. Thanks particularly to James Tompkin and Yun Fu for helping find these.

Friday, April 8, 2011

Applications

New update yesterday - now completed first draft of Applications, References, Algorithm and Problems up to chapter 9 and working on chapter 10. Various small errors found in earlier chapters and corrected.

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