Table of contents

  1. Front Matter
  2. Mario Mata, Jose Maria Armingol, Arturo de la Escalera
    Pages 1-55
  3. Mohammed Yeasin, Rajeev Sharma
    Pages 57-98
  4. Yu Sun, Ning Xi, Jindong Tan
    Pages 99-135
  5. Ma Jesús López Boada, Ramón Barber, Verónica Egido, Miguel Ángel Salichs
    Pages 137-165
  6. Gozde Unal, Anthony Yezzi, Hamid Krim
    Pages 167-202
  7. Johnny Park, Guilherme N. DeSouza
    Pages 203-264
  8. Christopher R. Wren
    Pages 265-324
  9. Hirotaka Asai, Takamasa Koshizen, Masataka Watanabe, Hiroshi Tsujin, Kazuyuki Aihara
    Pages 325-351

About this book

Introduction

This book presents some of the most recent research results in the area of machine learning and robot perception. The chapters represent new ways of solving real-world problems. The book covers topics such as intelligent object detection, foveated vision systems, online learning paradigms, reinforcement learning for a mobile robot, object tracking and motion estimation, 3D model construction, computer vision system and user modelling using dialogue strategies. This book will appeal to researchers, senior undergraduate/postgraduate students, application engineers and scientists.

Keywords

Navigation Tracking computer computer vision image processing intelligent object learning machine machine learning mobile robot model modeling perception reinforcement learning robot

Bibliographic information

  • DOI https://doi.org/10.1007/b137627
  • Copyright Information Springer-Verlag Berlin/Heidelberg 2005
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-26549-8
  • Online ISBN 978-3-540-32409-6
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • About this book
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