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© 2003

Robust Computer Vision

Theory and Applications

Book
  • 1.2k Downloads

Part of the Computational Imaging and Vision book series (CIVI, volume 26)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Nicu Sebe, Michael S. Lew
    Pages 1-23
  3. Nicu Sebe, Michael S. Lew
    Pages 25-59
  4. Nicu Sebe, Michael S. Lew
    Pages 61-82
  5. Nicu Sebe, Michael S. Lew
    Pages 83-110
  6. Nicu Sebe, Michael S. Lew
    Pages 111-134
  7. Nicu Sebe, Michael S. Lew
    Pages 135-162
  8. Nicu Sebe, Michael S. Lew
    Pages 163-197
  9. Back Matter
    Pages 199-215

About this book

Introduction

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."

Keywords

Active contour Bayesian network Hidden Markov Model Stereo Textur algorithms classification cognition computer vision database emotion emotion recognition learning machine learning perception

Authors and affiliations

  1. 1.LIACS Media LabLeiden UniversityLeidenThe Netherlands

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

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