Visual Analysis of Behaviour (eBook)

From Pixels to Semantics

Shaogang Gong, Tao Xiang (Autoren)

eBook Download: PDF

2011 | 2011
XIX, 356 Seiten
Springer London (Verlag)
978-0-85729-670-2 (ISBN)

Infos

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.

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Demand continues to grow worldwide, from both government and commerce, for technologies capable of automatically selecting and identifying object/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 "e;man-in-the-loop"e; active learning of behaviours; examines multi-camera behaviour correlation, person re-identification, and "e;connecting-the-dots"e; for global abnormal behaviour detection; discusses Bayesian information criterion, Bayesian networks, "e;bag-of-words"e; 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.

Inhalt

Part I: IntroductionAbout BehaviourBehaviour in ContextTowards Modelling BehaviourPart II: Single-Object BehaviourUnderstanding Facial ExpressionModelling GestureAction RecognitionPart III: Group BehaviourSupervised Learning of Group ActivityUnsupervised Behaviour ProfilingHierarchical Behaviour DiscoveryLearning Behavioural ContextModelling Rare and Subtle BehavioursMan in the LoopPart IV: Distributed BehaviourMulti-Camera Behaviour CorrelationPerson Re-IdentificationConnecting the DotsEpilogue

Produkt-Details

• Erscheint lt. Verlag: 26.5.2011
• Zusatzinfo: XIX, 356 p.
• Verlagsort: London
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Grafik / Design
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Sozialwissenschaften ► Politik / Verwaltung
• Schlagworte: activity recognition • Bayesian networks • biometrics • Facial Expression Modelling • Gait Recognition • Multimodal data fusion • Statistical Learning • Visual Behaviour Modelling • Visual Behaviour Representation • Visual Surveillance
• ISBN-10: 0-85729-670-1 / 0857296701
• ISBN-13: 978-0-85729-670-2 / 9780857296702