Analyzing Video Sequences of Multiple Humans

Tracking, Posture Estimation and Behavior Recognition

  • Jun Ohya
  • Akira Utsumi
  • Junji Yamato

Part of the The Kluwer International Series in Video Computing book series (VICO, volume 3)

Table of contents

  1. Front Matter
    Pages i-xxii
  2. Jun Ohya
    Pages 1-5
  3. Jun Ohya
    Pages 43-98
  4. Jun Ohya
    Pages 133-135
  5. Back Matter
    Pages 137-138

About this book

Introduction

Analyzing Video Sequences of Multiple Humans: Tracking, Posture Estimation and Behavior Recognition describes some computer vision-based methods that analyze video sequences of humans. More specifically, methods for tracking multiple humans in a scene, estimating postures of a human body in 3D in real-time, and recognizing a person's behavior (gestures or activities) are discussed. For the tracking algorithm, the authors developed a non-synchronous method that tracks multiple persons by exploiting a Kalman filter that is applied to multiple video sequences. For estimating postures, an algorithm is presented that locates the significant points which determine postures of a human body, in 3D in real-time. Human activities are recognized from a video sequence by the HMM (Hidden Markov Models)-based method that the authors pioneered. The effectiveness of the three methods is shown by experimental results.

Keywords

3D Virtual Environments Virtual Reality algorithms computer graphics computer vision graphics image processing pattern recognition video

Authors and affiliations

  • Jun Ohya
    • 1
  • Akira Utsumi
    • 2
  • Junji Yamato
    • 3
  1. 1.Waseda UniversityJapan
  2. 2.Advanced Telecommunications Research Institute InternationalJapan
  3. 3.Nippon Telegraph & Telephone CorporationJapan

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-1003-1
  • Copyright Information Kluwer Academic Publishers 2002
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-5346-1
  • Online ISBN 978-1-4615-1003-1
  • Series Print ISSN 1571-5205
  • About this book