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© 2013

Motion History Images for Action Recognition and Understanding

Benefits

  • Examines the state-of-the-art motion history image (MHI) method

  • Suitable for both undergraduate and graduate students familiar with basic image processing, and for researchers involved in human action and activity representation and recognition

  • The author has more than six years’ experience in this field

Book

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Md. A. R. Ahad
    Pages 1-18
  3. Md. Atiqur Rahman Ahad
    Pages 19-29
  4. Md. A. R. Ahad
    Pages 31-76
  5. Md. Atiqur Rahman Ahad
    Pages 77-85
  6. Back Matter
    Pages 87-121

About this book

Introduction

Human action analysis and recognition is a relatively mature field, yet one which is often not well understood by students and researchers.  The large number of possible variations in human motion and appearance, camera viewpoint, and environment, present considerable challenges.  Some important and common problems remain unsolved by the computer vision community. However, many valuable approaches have been proposed over the past decade, including the motion history image (MHI) method. This method has received significant attention, as it offers greater robustness and performance than other techniques. This work presents a comprehensive review of these state-of-the-art approaches and their applications, with a particular focus on the MHI method and its variants.

Keywords

Motion History Image (MHI)

Authors and affiliations

  1. 1.Faculty of EngineeringKyushu Institute of TechnologyKitakyushuJapan

Bibliographic information

  • Book Title Motion History Images for Action Recognition and Understanding
  • Authors Md. Atiqur Rahman Ahad
  • Series Title SpringerBriefs in Computer Science
  • DOI https://doi.org/10.1007/978-1-4471-4730-5
  • Copyright Information Md. Atiqur Rahman Ahad 2013
  • Publisher Name Springer, London
  • eBook Packages Computer Science Computer Science (R0)
  • Softcover ISBN 978-1-4471-4729-9
  • eBook ISBN 978-1-4471-4730-5
  • Series ISSN 2191-5768
  • Series E-ISSN 2191-5776
  • Edition Number 1
  • Number of Pages XVI, 116
  • Number of Illustrations 34 b/w illustrations, 0 illustrations in colour
  • Topics Pattern Recognition
  • Buy this book on publisher's site
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