This book presents a comprehensive treatment of visual analysis of behaviour from computational-modelling and algorithm-design perspectives. Topics: coverslearning-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 Bayesiannetworks, 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. Presents a comprehensive and unified treatment of visual analysis of behaviour from computational-modelling and algorithm-design perspectives. Provides analysis of current benchmarking databases and commercial systems. Includes a helpful list of acronyms. INDICE: Part I: Introduction. About Behaviour. Behaviour in Context. Towards Modelling Behaviour. Part II: Single-Object Behaviour. Understanding FacialExpression. Modelling Gesture. Action Recognition. Part III: Group Behaviour.Supervised Learning of Group Activity. Unsupervised Behaviour Profiling. Hierarchical Behaviour Discovery. Learning Behavioural Context. Modelling Rare andSubtle Behaviours. Man in the Loop. Part IV: Distributed Behaviour. Multi-Camera Behaviour Correlation. Person Re-Identification. Connecting the Dots. Epilogue.
- ISBN: 978-0-85729-669-6
- Editorial: Springer London
- Encuadernacion: Cartoné
- Páginas: 356
- Fecha Publicación: 27/05/2011
- Nº Volúmenes: 1
- Idioma: Inglés