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.
Reviews

From the reviews:

"The book aims to describe, analyze, and present the problem of visual analysis of behaviour of objects, with an emphasis on behaviour of people. I have thoroughly enjoyed going through the book and find it a strong contribution to the area of computer vision and automated visual analysis. ... The book is well suited for academics and researchers ... and would be a great resource for implementing any of the algorithms described therein." (Elena Corina Grigore, Perception, Vol. 42, 2013)

"This book presents a comprehensive introduction to algorithms and methodologies for representing, learning, recognizing, interpreting and predicting human behaviour, on the basis of visual data. Examples of human behaviour are given by facial expression, body gesture and human action. The book is mainly intended for readers interested in applications in the fields of visual surveillance, video indexing and search, robotics and healthcare, interaction, animation and computer games." (Patrizio Frosini, Zentralblatt MATH, Vol. 1238, 2012)



Book Information
ISBN 9780857296696
Author Shaogang Gong
Format Hardback
Page Count 356
Imprint Springer London Ltd
Publisher Springer London Ltd