推薦《Computer Vision: Models, Learning, and Inference》

推薦《Computer Vision:  Models, Learning, and Inference》

可以到這兒下載 http://www.computervisionmodels.com/

另附讀后感
《Computer vision：models，learning and inference》系列討論一
http://blog.sina.com.cn/s/blog_6bbd2dd10100svyx.html
《Computer vision：models，learning and inference》系列討論二
http://blog.sina.com.cn/s/blog_6bbd2dd10100t0ur.html

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