Overview
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."
The book, Robust Computer Vision: Theory and Applications (Computational Imaging and Vision #26) [Bulk, Wholesale, Quantity] ISBN#9789048162901 in Paperback by N. Sebe, M.S. Lew may be ordered in bulk quantities. Minimum starts at 25 copies. Availability based on publisher status and quantity being ordered.
Details
Format:
Paperback
Publication Date:
12/06/2010
ISBN-13:
9789048162901
Pages:
215
Publisher:
Springer Netherlands
