1. Home
  2. E-Book
  3. Visual Reconstruction

Visual Reconstruction by Andrew Blake, Andrew Zisserman

Visual Reconstruction

Visual Reconstruction by Andrew Blake, Andrew Zisserman
Visual Reconstruction by Andrew Blake, Andrew Zisserman
Publisher: The MIT Press 1987
ISBN/ASIN: 0262524066
ISBN-13: 9780262524063
Number of pages: 232
Visual Reconstruction presents a unified and highly original approach to the treatment of continuity in vision. It introduces, analyzes, and illustrates two new concepts. The first -- the weak continuity constraint -- is a concise, computational formalization of piecewise continuity. It is a mechanism for expressing the expectation that visual quantities such as intensity, surface color, and surface depth vary continuously almost everywhere, but with occasional abrupt changes. The second concept -- the graduated nonconvexity algorithm -- arises naturally from the first. It is an efficient, deterministic (nonrandom) algorithm for fitting piecewise continuous functions to visual data.
Computers & Internet Computer Science Artificial Intelligence Computer Vision
Go To Read/Download Page
Home Page

More Free E-Books For Artificial Intelligence

Similar Books For Artificial Intelligence

1. Applied Artificial Neural Networks by Christian Dawson
2. How Mobile Robots Can Self-organise a Vocabulary by Paul Vogt
3. Statistical Foundations of Machine Learning by Gianluca Bontempi, Souhaib Ben Taieb
4. Probabilistic Models in the Study of Language by Roger Levy
5. Computer Vision Metrics: Survey, Taxonomy, and Analysis by Scott Krig
6. Statistical Learning and Sequential Prediction by Alexander Rakhlin, Karthik Sridharan
7. Neural Network Design by Martin T. Hagan, et al.
8. Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz, Shai Ben-David
9. The Playful Machine by Ralf Der, Georg Martius
10. Deep Learning Tutorial by LISA lab
11. Voice Communication with Computers: Conversational Systems by C. Schmandt
12. Lecture Notes in Machine Learning by Zdravko Markov
13. Machine Learning and Data Mining: Lecture Notes by Aaron Hertzmann
14. Learning Deep Architectures for AI by Yoshua Bengio
15. An Introduction to Statistical Learning by G. James, D. Witten, T. Hastie, R. Tibshirani
16. Deep Learning in Neural Networks: An Overview by Juergen Schmidhuber
17. 3D Video Processing and Transmission Fundamentals by Chaminda Hewage
18. Deep Learning by Yoshua Bengio, Ian Goodfellow, Aaron Courville
19. Algorithms for Reinforcement Learning by Csaba Szepesvari
20. Neural Networks and Deep Learning by Michael Nielsen
21. Neural Networks by Milan Hajek
22. A Survey of Statistical Network Models by A. Goldenberg, A.X. Zheng, S.E. Fienberg, E.M. Airoldi
23. Machine Learning: The Complete Guide by
24. Modern Robotics with OpenCV by Widodo Budiharto
25. Introduction to Machine Learning by Alex Smola, S.V.N. Vishwanathan
26. Notes on Elementary Spectral Graph Theory by Jean Gallier
27. An Introductory Study on Time Series Modeling and Forecasting by Ratnadip Adhikari, R. K. Agrawal
28. The LION Way: Machine Learning plus Intelligent Optimization by Roberto Battiti, Mauro Brunato
29. A Course in Machine Learning by Hal Daumé III
30. Natural Language Processing for Prolog Programmers by Michael A. Covington
31. Fundamentals of Image Processing by Hany Farid
32. A First Encounter with Machine Learning by Max Welling
33. Object Detection in Real Images by Dilip K. Prasad
34. Artificial Neural Networks: Architectures and Applications by Kenji Suzuki (ed.)
35. Modern Speech Recognition Approaches with Case Studies by S. Ramakrishnan (ed.)
36. Artificial Neural Networks by
37. Current Advancements in Stereo Vision by Asim Bhatti (ed.)
38. An Introduction to Computational Neuroscience by Todd Troyer
39. Machine Translation: an Introductory Guide by Doug Arnold, at al.
40. Programming Computer Vision with Python by Jan Erik Solem
41. Computer Vision: Models, Learning, and Inference by Simon J.D. Prince
42. A Mathematical Introduction to Robotic Manipulation by Richard M. Murray, Zexiang Li, S. Shankar Sastry
43. Natural Language Processing with Python by Steven Bird, Ewan Klein, Edward Loper
44. Digital Image Processing by Stefan G. Stanciu
45. An Introduction to Stochastic Attribute-Value Grammars by Rob Malouf, Miles Osborne
46. Formal Language Theory for Natural Language Processing by Shuly Wintner
47. Image Processing in Optical Coherence Tomography using Matlab by Robert Koprowski, Zygmunt Wrobel
48. Natural Language Processing for the Working Programmer by Daniël de Kok, Harm Brouwer
49. Advances in Stereo Vision by Jose R.A. Torreao
50. An Introduction to Neural Networks by Ben Krose, Patrick van der Smagt

Free E-Books For Computers & Internet
Free E-Books For Computer Science
Free E-Books For Artificial Intelligence
Free E-Books For Computer Vision



Categories