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Visual Analysis of Behaviour

From Pixels to Semantics

  • Shaogang Gong
  • Tao Xiang

Table of contents

  1. Front Matter
    Pages I-XIX
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. Shaogang Gong, Tao Xiang
      Pages 3-13
    3. Shaogang Gong, Tao Xiang
      Pages 15-37
    4. Shaogang Gong, Tao Xiang
      Pages 39-65
  3. Single-Object Behaviour

    1. Front Matter
      Pages 67-67
    2. Shaogang Gong, Tao Xiang
      Pages 69-93
    3. Shaogang Gong, Tao Xiang
      Pages 95-131
    4. Shaogang Gong, Tao Xiang
      Pages 133-160
  4. Group Behaviour

    1. Front Matter
      Pages 161-161
    2. Shaogang Gong, Tao Xiang
      Pages 163-192
    3. Shaogang Gong, Tao Xiang
      Pages 193-213
    4. Shaogang Gong, Tao Xiang
      Pages 215-232
    5. Shaogang Gong, Tao Xiang
      Pages 233-249
    6. Shaogang Gong, Tao Xiang
      Pages 251-266
    7. Shaogang Gong, Tao Xiang
      Pages 267-282
  5. Distributed Behaviour

    1. Front Matter
      Pages 283-283
    2. Shaogang Gong, Tao Xiang
      Pages 285-299
    3. Shaogang Gong, Tao Xiang
      Pages 301-313
    4. Shaogang Gong, Tao Xiang
      Pages 315-341

About this book

Introduction

Demand continues to grow worldwide, from both government and commerce, for technologies capable of automatically selecting and identifying object and human behaviour.

This accessible text/reference presents a comprehensive and unified treatment of visual analysis of behaviour from computational-modelling and algorithm-design perspectives. The book provides in-depth discussion on computer vision and statistical machine learning techniques, in addition to reviewing a broad range of behaviour modelling problems. A mathematical background is not required to understand the content, although readers will benefit from modest knowledge of vectors and matrices, eigenvectors and eigenvalues, linear algebra, optimisation, multivariate analysis, probability, statistics and calculus.

Topics and features:

  • Provides a thorough introduction to the study and modelling of behaviour, and a concluding epilogue
  • Covers learning-group activity models, unsupervised behaviour profiling, hierarchical behaviour discovery, learning behavioural context, modelling rare behaviours, and “man-in-the-loop” active learning of behaviours
  • Examines multi-camera behaviour correlation, person re-identification, and “connecting-the-dots” for global abnormal behaviour detection
  • Discusses Bayesian information criterion, static Bayesian graph models, “bag-of-words” representation, canonical correlation analysis, dynamic Bayesian networks, Gaussian mixtures, and Gibbs sampling
  • Investigates hidden conditional random fields, hidden Markov models, human silhouette shapes, latent Dirichlet allocation, local binary patterns, locality preserving projection, and Markov processes
  • Explores probabilistic graphical models, probabilistic topic models, space-time interest points, spectral clustering, and support vector machines
  • Includes a helpful list of acronyms

A valuable resource for both researchers in computer vision and machine learning, and for developers of commercial applications, the book can also serve as a useful reference for postgraduate students of computer science and behavioural science. Furthermore, policymakers and commercial managers will find this an informed guide on intelligent video analytics systems.

Dr. Shaogang Gong is a Professor of Visual Computation in the School of Electronic Engineering and Computer Science at Queen Mary University of London, UK. Dr. Tao Xiang is a Lecturer at the same institution.

Keywords

Activity Recognition Bayesian Networks Biometrics Facial Expression Modelling Gait Recognition Multimodal Data Fusion Statistical Learning Visual Behaviour Modelling Visual Behaviour Representation Visual Surveillance

Authors and affiliations

  • Shaogang Gong
    • 1
  • Tao Xiang
    • 2
  1. 1.Dept. Computer ScienceQueen Mary University of LondonLondonUnited Kingdom
  2. 2.Dept. Computer ScienceQueen Mary University of LondonLondonUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-85729-670-2
  • Copyright Information Springer-Verlag London Limited 2011
  • Publisher Name Springer, London
  • eBook Packages Computer Science
  • Print ISBN 978-0-85729-669-6
  • Online ISBN 978-0-85729-670-2
  • Buy this book on publisher's site