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Visual Analysis of Behaviour: From Pixels to Semantics,Used
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This book presents a comprehensive treatment of visual analysis of behaviour from computationalmodelling and algorithmdesign perspectives. Topics: covers learninggroup activity models, unsupervised behaviour profiling, hierarchical behaviour discovery, learning behavioural context, modelling rare behaviours, and manintheloop active learning; examines multicamera behaviour correlation, person reidentification, and connectingthedots for abnormal behaviour detection; discusses Bayesian information criterion, Bayesian networks, bagofwords 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, spacetime interest points, spectral clustering, and support vector machines.
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