Access this book
Tax calculation will be finalised at checkout
Other ways to access
About this book
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."
Similar content being viewed by others
Keywords
Table of contents (7 chapters)
Authors and Affiliations
About the authors
Nicu Sebe received his PhD degree from Leiden University in 2001. Currently, he is an Assistant Professor at Leiden University in the Netherlands. His main interest is in the fields of computer vision and pattern recognition, in particular content-based retrieval and robust techniques in computer vision. He was co-editing the proceedings of the International Conference on Image and Video Retrieval 2002. He is also acting as the technical program co-chair for the International Conference on Image and Video Retrieval 2003.
Michael S. Lew received his PhD degree in Electrical Engineering from the University of Illinois at Urbana-Champaign. He is currently an Associate Professor at Leiden University in the Netherlands. He has published over 100 scientific papers and helped organize several large conferences including IEEE Multimedia, ACM Multimedia, and the International Conference on Image and Video Retrieval.
Bibliographic Information
Book Title: Robust Computer Vision
Book Subtitle: Theory and Applications
Authors: Nicu Sebe, Michael S. Lew
Series Title: Computational Imaging and Vision
DOI: https://doi.org/10.1007/978-94-017-0295-9
Publisher: Springer Dordrecht
-
eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media Dordrecht 2003
Hardcover ISBN: 978-1-4020-1293-8Published: 30 April 2003
Softcover ISBN: 978-90-481-6290-1Published: 06 December 2010
eBook ISBN: 978-94-017-0295-9Published: 29 June 2013
Series ISSN: 1381-6446
Edition Number: 1
Number of Pages: XV, 215
Topics: Computer Imaging, Vision, Pattern Recognition and Graphics, Artificial Intelligence, Data Structures and Information Theory, Multimedia Information Systems, Information Storage and Retrieval