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Machine Learning in Computer Vision

  • Book
  • © 2005

Overview

Authors:
  1. N. Sebe

    1. University of Amsterdam, The Netherlands

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  2. Ira Cohen

    1. HP Research Labs, USA

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  3. Ashutosh Garg

    1. Google Inc., USA

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  4. Thomas S. Huang

    1. University of Illinois at Urbana-Champaign, Urbana, USA

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  • Researchers in Computer Vision has found, in recent years, that Machine Learning tools are extremely powerful. Thus, all in the CV communication should acquire expertise in ML. Our book is the first and currently only one that presents the most important methods of ML in CV.
  • Our book presents not only theories, but also algorithms and applications. Thus, it is useful for practitioners as well as graduate students.

Part of the book series: Computational Imaging and Vision (CIVI, volume 29)

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-xv
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  2. Introduction

    Pages 1-13

  3. Theory: Probabilistic Classifiers

    Pages 15-43

  4. Theory: Generalization Bounds

    Pages 45-64

  5. Theory: Semi-Supervised Learning

    Pages 65-101

  6. Algorithm: Maximum Likelihood Minimum Entropy HMM

    Pages 103-118

  7. Algorithm: Margin Distribution Optimization

    Pages 119-128

  8. Algorithm: Learning the Structure of Bayesian Network Classifiers

    Pages 129-156

  9. Application: Office Activity Recognition

    Pages 157-173

  10. Application: Multimodal Event Detection

    Pages 175-186

  11. Application: Facial Expression Recognition

    Pages 187-209

  12. Application: Bayesian Network Classifiers for Face Detection

    Pages 211-224

  13. Back Matter

    Pages 225-242
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Reviews

"This book comes right on time [...] It is amazing so early in a new field that a book appears which connects theory to algorithms and through them to convincing applications. [...] This book will surely be with us for quite some time to come."
From the foreword by Arnold Smeulders

Authors and Affiliations

  • University of Amsterdam, The Netherlands

    N. Sebe

  • HP Research Labs, USA

    Ira Cohen

  • Google Inc., USA

    Ashutosh Garg

  • University of Illinois at Urbana-Champaign, Urbana, USA

    Thomas S. Huang

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