Non-overlapping distributed tracking using particle filter
Tracking people or objects across multiple cameras is a challenging research area in visual computing especially when these cameras have non-overlapping field-of-views. The important task is to associate a target of interest with its previous appearances across time and space within the camera netwo...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
IEEE Coputer Society Conference Publishing Services
2006
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| Online Access: | http://hdl.handle.net/20.500.11937/45185 |
| _version_ | 1848757212956065792 |
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| author | Leoputra, Wilson Tan, Tele Lim, Fee-Lee |
| author2 | Y.Y. Tang |
| author_facet | Y.Y. Tang Leoputra, Wilson Tan, Tele Lim, Fee-Lee |
| author_sort | Leoputra, Wilson |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Tracking people or objects across multiple cameras is a challenging research area in visual computing especially when these cameras have non-overlapping field-of-views. The important task is to associate a target of interest with its previous appearances across time and space within the camera network. In this paper, we propose a unified tracking framework using particle filter to efficiently switch between track prediction (to deal with non-overlapping region tracking) and visual tracking. The particle filter tracking system uses a map to provide the possible trajectory information of the target as it moves within the non-overlapping regions. We implemented and tested this tracking approach in an in-house multiple cameras system. Promising results were obtained which suggested the feasibility of such an approach. |
| first_indexed | 2025-11-14T09:24:31Z |
| format | Conference Paper |
| id | curtin-20.500.11937-45185 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:24:31Z |
| publishDate | 2006 |
| publisher | IEEE Coputer Society Conference Publishing Services |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-451852023-02-27T07:34:29Z Non-overlapping distributed tracking using particle filter Leoputra, Wilson Tan, Tele Lim, Fee-Lee Y.Y. Tang S.P.Wang G. Lorette D.S. Young H. Yang Tracking people or objects across multiple cameras is a challenging research area in visual computing especially when these cameras have non-overlapping field-of-views. The important task is to associate a target of interest with its previous appearances across time and space within the camera network. In this paper, we propose a unified tracking framework using particle filter to efficiently switch between track prediction (to deal with non-overlapping region tracking) and visual tracking. The particle filter tracking system uses a map to provide the possible trajectory information of the target as it moves within the non-overlapping regions. We implemented and tested this tracking approach in an in-house multiple cameras system. Promising results were obtained which suggested the feasibility of such an approach. 2006 Conference Paper http://hdl.handle.net/20.500.11937/45185 10.1109/ICPR.2006.862 IEEE Coputer Society Conference Publishing Services restricted |
| spellingShingle | Leoputra, Wilson Tan, Tele Lim, Fee-Lee Non-overlapping distributed tracking using particle filter |
| title | Non-overlapping distributed tracking using particle filter |
| title_full | Non-overlapping distributed tracking using particle filter |
| title_fullStr | Non-overlapping distributed tracking using particle filter |
| title_full_unstemmed | Non-overlapping distributed tracking using particle filter |
| title_short | Non-overlapping distributed tracking using particle filter |
| title_sort | non-overlapping distributed tracking using particle filter |
| url | http://hdl.handle.net/20.500.11937/45185 |