Recognising behaviours of multiple people with hierarchical probabilistic model and statistical data association
Recognising behaviours of multiple people, especially high-level behaviours, is an important task in surveillance systems. When the reliable assignment of people to the set of observations is unavailable, this task becomes complicated. To solve this task, we present an approach, in which the hierarc...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
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The British Machine Vision Association and Society for Pattern Recognition
2006
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| Online Access: | http://www.macs.hw.ac.uk/bmvc2006/papers/190.pdf http://hdl.handle.net/20.500.11937/15276 |
| _version_ | 1848748849781276672 |
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| author | Nguyen, Nam Venkatesh, Svetha Bui, H.H. |
| author2 | M. Chantler |
| author_facet | M. Chantler Nguyen, Nam Venkatesh, Svetha Bui, H.H. |
| author_sort | Nguyen, Nam |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Recognising behaviours of multiple people, especially high-level behaviours, is an important task in surveillance systems. When the reliable assignment of people to the set of observations is unavailable, this task becomes complicated. To solve this task, we present an approach, in which the hierarchical hidden Markov model (HHMM) is used for modeling the behaviour of each person and the joint probabilistic data association filters (JPD AF) is applied for data association. The main contributions of this paper lie in the integration of multiple HHMMs for recognising high-le v el behaviours of multiple people and the construction of the Rao-Blackwellised particle filters (RBPF) for approximate inference. Preliminary experimental results in a real environment show the robustness of our integrated method in behaviour recognition and its advantage over the use of Kalman filter in tracking people. |
| first_indexed | 2025-11-14T07:11:35Z |
| format | Conference Paper |
| id | curtin-20.500.11937-15276 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:11:35Z |
| publishDate | 2006 |
| publisher | The British Machine Vision Association and Society for Pattern Recognition |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-152762022-10-20T07:26:56Z Recognising behaviours of multiple people with hierarchical probabilistic model and statistical data association Nguyen, Nam Venkatesh, Svetha Bui, H.H. M. Chantler R. Fisher E. Trucco Recognising behaviours of multiple people, especially high-level behaviours, is an important task in surveillance systems. When the reliable assignment of people to the set of observations is unavailable, this task becomes complicated. To solve this task, we present an approach, in which the hierarchical hidden Markov model (HHMM) is used for modeling the behaviour of each person and the joint probabilistic data association filters (JPD AF) is applied for data association. The main contributions of this paper lie in the integration of multiple HHMMs for recognising high-le v el behaviours of multiple people and the construction of the Rao-Blackwellised particle filters (RBPF) for approximate inference. Preliminary experimental results in a real environment show the robustness of our integrated method in behaviour recognition and its advantage over the use of Kalman filter in tracking people. 2006 Conference Paper http://hdl.handle.net/20.500.11937/15276 http://www.macs.hw.ac.uk/bmvc2006/papers/190.pdf The British Machine Vision Association and Society for Pattern Recognition restricted |
| spellingShingle | Nguyen, Nam Venkatesh, Svetha Bui, H.H. Recognising behaviours of multiple people with hierarchical probabilistic model and statistical data association |
| title | Recognising behaviours of multiple people with hierarchical probabilistic model and statistical data association |
| title_full | Recognising behaviours of multiple people with hierarchical probabilistic model and statistical data association |
| title_fullStr | Recognising behaviours of multiple people with hierarchical probabilistic model and statistical data association |
| title_full_unstemmed | Recognising behaviours of multiple people with hierarchical probabilistic model and statistical data association |
| title_short | Recognising behaviours of multiple people with hierarchical probabilistic model and statistical data association |
| title_sort | recognising behaviours of multiple people with hierarchical probabilistic model and statistical data association |
| url | http://www.macs.hw.ac.uk/bmvc2006/papers/190.pdf http://hdl.handle.net/20.500.11937/15276 |