Motion-Based Recognition

  • Mubarak Shah
  • Ramesh Jain

Part of the Computational Imaging and Vision book series (CIVI, volume 9)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Visual Recognition of Activities, Gestures, Facial Expressions and Speech: An Introduction and a Perspective

  3. Human Activity Recognition

    1. Front Matter
      Pages 15-15
    2. Adam Baumberg, David Hogg
      Pages 39-60
    3. Steven M. Seitz, Charles R. Dyer
      Pages 61-85
    4. Ramprasad Polana, Randal Nelson
      Pages 87-124
    5. Aaron F. Bobick, James W. Davis
      Pages 125-146
    6. Nigel H. Goddard
      Pages 147-170
  4. Gesture Recognition and Facial Expression Recognition

    1. Front Matter
      Pages 199-199
    2. Aaron F. Bobick, Andrew D. Wilson
      Pages 201-226
    3. Michael J. Black, Yaser Yacoob, Shanon X. Ju
      Pages 245-269
    4. Irfan Essa, Alex Pentland
      Pages 271-298
  5. Lipreading

    1. Front Matter
      Pages 299-299
    2. Christoph Bregler, Stephen M. Omohundro
      Pages 301-320
    3. Alan J. Goldschen, Oscar N. Garcia, Eric D. Petajan
      Pages 321-343
    4. Nan Li, Shawn Dettmer, Mubarak Shah
      Pages 345-371
  6. Back Matter
    Pages 373-373

About this book

Introduction

Motion-based recognition deals with the recognition of an object and/or its motion, based on motion in a series of images. In this approach, a sequence containing a large number of frames is used to extract motion information. The advantage is that a longer sequence leads to recognition of higher level motions, like walking or running, which consist of a complex and coordinated series of events. Unlike much previous research in motion, this approach does not require explicit reconstruction of shape from the images prior to recognition.
This book provides the state-of-the-art in this rapidly developing discipline. It consists of a collection of invited chapters by leading researchers in the world covering various aspects of motion-based recognition including lipreading, gesture recognition, facial expression recognition, gait analysis, cyclic motion detection, and activity recognition.
Audience: This volume will be of interest to researchers and post- graduate students whose work involves computer vision, robotics and image processing.

Keywords

Hidden Markov Model Optical flow computer vision image processing learning robot robotics speech recognition

Editors and affiliations

  • Mubarak Shah
    • 1
  • Ramesh Jain
    • 2
  1. 1.Computer Vision Laboratory, Computer Science DepartmentUniversity of Central FloridaOrlandoUSA
  2. 2.Electrical and Computer EngineeringUniversity of California, San DiegoSan DiegoUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-015-8935-2
  • Copyright Information Springer Science+Business Media B.V. 1997
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-90-481-4870-7
  • Online ISBN 978-94-015-8935-2
  • Series Print ISSN 1381-6446
  • About this book
Industry Sectors
Pharma
Automotive
Biotechnology
Electronics
Telecommunications
Consumer Packaged Goods
Energy, Utilities & Environment
Aerospace