© 2008

Machine Learning Techniques for Multimedia

Case Studies on Organization and Retrieval

  • Matthieu Cord
  • Pádraig Cunningham

Part of the Cognitive Technologies book series (COGTECH)

Table of contents

  1. Front Matter
    Pages I-XVI
  2. Introduction to Learning Principles for Multimedia Data

    1. Front Matter
      Pages 1-1
    2. Simon P. Wilson, Rozenn Dahyot, Pádraig Cunningham
      Pages 3-19
    3. Pádraig Cunningham, Matthieu Cord, Sarah Jane Delany
      Pages 21-49
    4. Derek Greene, Pádraig Cunningham, Rudolf Mayer
      Pages 51-90
    5. Pádraig Cunningham
      Pages 91-112
  3. Multimedia Applications

    1. Front Matter
      Pages 113-113
    2. Matthieu Cord, Philippe-Henri Gosselin
      Pages 115-138
    3. Peter M. Roth, Horst Bischof
      Pages 139-158
    4. Roberto Valenti, Nicu Sebe, Theo Gevers, Ira Cohen
      Pages 159-187
    5. Simon P. Wilson, Julien Fauqueur, Nozha Boujemaa
      Pages 189-204
    6. Pinar Duygulu, Muhammet Baştan, Derya Ozkan
      Pages 205-225
  4. Back Matter
    Pages 287-288

About this book


Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Applying machine learning techniques to multimedia content involves special considerations – the data is typically of very high dimension, and the normal distinction between supervised and unsupervised techniques does not always apply.

This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains such as image retrieval, biometrics, semantic labelling, mobile devices, and mining in text and music.

This book will be suitable for practitioners, researchers and students engaged with machine learning in multimedia applications.


Dimensionsreduktion biometrics classification clustering cognition database decision theory learning machine learning multimedia pattern recognition performance supervised learning unsupervised learning video

Editors and affiliations

  • Matthieu Cord
    • 1
  • Pádraig Cunningham
    • 2
  1. 1.UPMC University, CNRS (UMR 7606) Lab. LIP6France
  2. 2.University College Dublin, School of Computer Science & InformaticsBelfieldIreland

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