Prince, Simon J. D, <br/><br/>
Computer vision :  models, learning, and inference / 
Simon J.D. Prince. 
 - xviii, 579 páginas :  ilustraciones. 
<br/><br/> Varían los años de reimpresión 
<br/><br/>Incluye bibliografía 
<br/><br/>Machine generated contents note: Part I. Probability: 1. Introduction to probability; 2. Common probability distributions; 3. Fitting probability models; 4. The normal distribution; Part II. Machine Learning for Machine Vision: 5. Learning and inference in vision; 6. Modeling complex data densities; 7. Regression models; 8. Classification models; Part III. Connecting Local Models: 9. Graphical models; 10. Models for chains and trees; 11. Models for grids; Part IV. Preprocessing: 12. Image preprocessing and feature extraction; Part V. Models for Geometry: 13. The pinhole camera; 14. Models for transformations; 15. Multiple cameras; Part VI. Models for Vision: 16. Models for style and identity; 17. Temporal models; 18. Models for visual words; Part VII. Appendices: A. Optimization; B. Linear algebra; C. Algorithms. 
<br/><br/><label>ISBN: </label>1107011795 9781107011793 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Computadores.<br/>Visión por computador.
<br/><br/><label>Dewey Class. No.: </label>006.37  / P954c 2017