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Visual Analysis of Behaviour

From Pixels to Semantics

By Shaogang Gong , Tao Xiang

  • eBook Price: $119.00
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This book explores visual analysis of behaviour from computational-modeling and algorithm-design perspectives, covering learning-group activity models, unsupervised behaviour profiling, hierarchical behaviour discovery, modelling rare behaviours, and more.

Full Description

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  • ISBN13: 978-0-8572-9669-6
  • 375 Pages
  • User Level: Science
  • Publication Date: May 26, 2011
  • Available eBook Formats: PDF

Related Titles

  • Information Systems and Neuroscience
Full Description
This book presents a comprehensive treatment of visual analysis of behaviour from computational-modelling and algorithm-design perspectives. Topics: covers learning-group activity models, unsupervised behaviour profiling, hierarchical behaviour discovery, learning behavioural context, modelling rare behaviours, and “man-in-the-loop” active learning; examines multi-camera behaviour correlation, person re-identification, and “connecting-the-dots” for abnormal behaviour detection; discusses Bayesian information criterion, Bayesian networks, “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.
Table of Contents

Table of Contents

  1. Part I: Introduction.
  2. About Behaviour.
  3. Behaviour in Context.
  4. Towards Modelling Behaviour.
  5. Part II: Single
  6. Object Behaviour.
  7. Understanding Facial Expression.
  8. Modelling Gesture.
  9. Action Recognition.
  10. Part III: Group Behaviour.
  11. Supervised Learning of Group Activity.
  12. Unsupervised Behaviour Profiling.
  13. Hierarchical Behaviour Discovery.
  14. Learning Behavioural Context.
  15. Modelling Rare and Subtle Behaviours.
  16. Man in the Loop.
  17. Part IV: Distributed Behaviour.
  18. Multi
  19. Camera Behaviour Correlation.
  20. Person Re
  21. Identification.
  22. Connecting the Dots.
  23. Epilogue.

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