Computer Vision Models: Update

Saturday, October 16, 2010

Update

Since Thursdays version quite a lot of stuff has changed. I've finished my (horrible) first draft of the text on pre-processing images. I've worked on my (horrible) first draft of the text on subspace models. I've made some figures for the subspace models chapter. I've corrected some small errors in Chapters 3,5,6,7. I've added figures explaining the relationship between the models in chapters 7 and 8. I've done some serious editing to chapter 8.

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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