ENGLISH

Robust Computer Vision: Theory and Applications

By Nicu Sebe , Michael S. Lew (auth.)

Book information

Publisher
Springer Netherlands
Year
2003
ISBN
978-90-481-6290-1, 978-94-017-0295-9
DOI
10.1007/978-94-017-0295-9
Language
english
Format
PDF
Filesize
7 MB (7329802 bytes)
Series
Computational Imaging and Vision 26
Edition
1
Pages
215\226
Orientation
yes
Scanned
yes
Time added
2013-08-01 04:00:00
Computer ImagingCryptology and Information Theory; Multimedia InfoPattern Recognition and Graphics; Artificial IntelVision

Description

From the foreword by Thomas Huang: "During the past decade, researchers in computer vision have found that probabilistic machine learning methods are extremely powerful. This book describes some of these methods. In addition to the Maximum Likelihood framework, Bayesian Networks, and Hidden Markov models are also used. Three aspects are stressed: features, similarity metric, and models. Many interesting and important new results, based on research by the authors and their collaborators, are presented. Although this book contains many new results, it is written in a style that suits both experts and novices in computer vision."

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