Computer Vision Models: Final Version

Friday, September 23, 2011

Final Version

The final version of the book is now online. I've fixed a lot of mistakes in the last couple of weeks and I've written a proper introductory chapter. I've managed to decrease the size of the file a little too. The book has now been submitted to the publisher, but please mail me if you find any errata - I'm sure there are still loads. I can still correct things when I get the proofs (around December, apparently).

2 comments:

Ahmad H.September 24, 2011 at 5:12 PM
Congrats Simon! This is truly brilliant.

I think you can now breathe in satisfaction :)
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Kourosh MeshgiOctober 14, 2011 at 4:43 AM
Hi
I just want to thank you for the effort you've made. I'm gonna read your book (currently downloading). By the way I am a PhD student currently working in the field of Machine Vision.
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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