Towards behaviour recognition based video surveillance

Shaogang Gong

doi:10.1117/12.577153

16 December 2004 Towards behaviour-recognition-based video surveillance

Shaogang Gong

Proceedings Volume 5616, Optics and Photonics for Counterterrorism and Crime Fighting; (2004) https://doi.org/10.1117/12.577153
Event: European Symposium on Optics and Photonics for Defence and Security, 2004, London, United Kingdom

Abstract

We present the latest results on learnable stochastic temporal models for automatic event and behaviour recognition in CCTV surveillance video. We introduce a novel approach to modelling and recognising complex activities involving simultaneous movement of multiple objects. Our approach differs from most previous work in that the visual understanding of activity is based on visual event detection and reasoning instead of object tracking and trajectory matching. Dynamic probabilistic graph models are exploited for modelling the temporal relationships among a set of different object temporal events. Typical applications of this technology include automatic semantic video content analysis, profiling and indexing of salient event and behaviour captured in CCTV video, and the early recognition of atypical behaviour in scenes where such behaviour could lead to a threat to safety.

Citation Download Citation

Shaogang Gong "Towards behaviour-recognition-based video surveillance", Proc. SPIE 5616, Optics and Photonics for Counterterrorism and Crime Fighting, (16 December 2004); https://doi.org/10.1117/12.577153

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available