Gong / Xiang Visual Analysis of Behaviour

From Pixels to Semantics
2011
ISBN: 978-0-85729-670-2
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 356 Seiten, eBook

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.

Zielgruppe

Research

Autoren/Hrsg.

Gong, Shaogang

Xiang, Tao

Inhaltsverzeichnis

Part I: Introduction

About Behaviour

Behaviour in Context

Towards Modelling Behaviour

Part II: Single-Object Behaviour

Understanding Facial Expression

Modelling Gesture

Action Recognition

Part III: Group Behaviour

Supervised Learning of Group Activity

Unsupervised Behaviour Profiling

Hierarchical Behaviour Discovery

Learning Behavioural Context

Modelling Rare and Subtle Behaviours

Man in the Loop

Part IV: Distributed Behaviour

Multi-Camera Behaviour Correlation

Person Re-Identification

Connecting the Dots

Epilogue