venkatesh-recognisingand-2003.pdf (328.11 kB)
Recognising and monitoring high-level behaviours in complex spatial environments
conference contribution
posted on 2003-01-01, 00:00 authored by N Nguyen, H Bui, Svetha VenkateshSvetha Venkatesh, G WestThe recognition of activities from sensory data is important in advanced surveillance systems to enable prediction of high-level goals and intentions of the target under surveillance. The problem is complicated by sensory noise and complex activity spanning large spatial and temporal extents. This paper presents a system for recognising high-level human activities from multi-camera video data in complex spatial environments. The Abstract Hidden Markov mEmory Model (AHMEM) is used to deal with noise and scalability The AHMEM is an extension of the Abstract Hidden Markov Model (AHMM) that allows us to represent a richer class of both state-dependent and context-free behaviours. The model also supports integration with low-level sensory models and efficient probabilistic inference. We present experimental results showing the ability of the system to perform real-time monitoring and recognition of complex behaviours of people from observing their trajectories within a real, complex indoor environment.
History
Event
Conference on Computer Vision and Pattern Recognition (2003 : Madison, Wis.)Pagination
620 - 625Publisher
IEEELocation
Madison, Wis.Place of publication
Los Alamitos, Calif.Publisher DOI
Start date
2003-06-18End date
2003-06-20ISSN
1063-6919ISBN-13
9780769519005ISBN-10
0769519008Language
engNotes
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.Publication classification
E1.1 Full written paper - refereedCopyright notice
2003, IEEETitle of proceedings
CVPR 2003 : Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern RecognitionUsage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC