Visual tracking of multiple targets by Multi-Bernoulli filtering of background subtracted image data
Most visual multi-target tracking techniques in the literature employ a detection routine to map the image data to point measurements that are usually further processed by a filter. In this paper, we present a visual tracking technique based on a multi-target filtering algorithm that operates direct...
| Main Authors: | , , |
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| Format: | Book Chapter |
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Springer
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/45604 |
| _version_ | 1848757332655210496 |
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| author | Hoseinnezhad, R. Vo, Ba-Ngu Vu, T.N. |
| author2 | Ying Tan |
| author_facet | Ying Tan Hoseinnezhad, R. Vo, Ba-Ngu Vu, T.N. |
| author_sort | Hoseinnezhad, R. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Most visual multi-target tracking techniques in the literature employ a detection routine to map the image data to point measurements that are usually further processed by a filter. In this paper, we present a visual tracking technique based on a multi-target filtering algorithm that operates directly on the image observations and does not require any detection nor training patterns. Instead, we use the recent history of image data for non-parametric background subtraction and apply an efficient multi-target filtering technique, known as the multi-Bernoulli filter, on the resulting grey scale image data. In our experiments, we applied our method to track multiple people in three video sequences from the CAVIAR dataset. The results show that our method can automatically track multiple interacting targets and quickly finds targets entering or leaving the scene. |
| first_indexed | 2025-11-14T09:26:25Z |
| format | Book Chapter |
| id | curtin-20.500.11937-45604 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:26:25Z |
| publishDate | 2011 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-456042023-02-02T07:57:34Z Visual tracking of multiple targets by Multi-Bernoulli filtering of background subtracted image data Hoseinnezhad, R. Vo, Ba-Ngu Vu, T.N. Ying Tan Yuhui Shi Yi Chai Guoyin Wang multi-Bernoulli multi-target tracking Bayesian estimation random finite sets visual tracking Most visual multi-target tracking techniques in the literature employ a detection routine to map the image data to point measurements that are usually further processed by a filter. In this paper, we present a visual tracking technique based on a multi-target filtering algorithm that operates directly on the image observations and does not require any detection nor training patterns. Instead, we use the recent history of image data for non-parametric background subtraction and apply an efficient multi-target filtering technique, known as the multi-Bernoulli filter, on the resulting grey scale image data. In our experiments, we applied our method to track multiple people in three video sequences from the CAVIAR dataset. The results show that our method can automatically track multiple interacting targets and quickly finds targets entering or leaving the scene. 2011 Book Chapter http://hdl.handle.net/20.500.11937/45604 10.1007/978-3-642-21524-7_63 Springer restricted |
| spellingShingle | multi-Bernoulli multi-target tracking Bayesian estimation random finite sets visual tracking Hoseinnezhad, R. Vo, Ba-Ngu Vu, T.N. Visual tracking of multiple targets by Multi-Bernoulli filtering of background subtracted image data |
| title | Visual tracking of multiple targets by Multi-Bernoulli filtering of background subtracted image data |
| title_full | Visual tracking of multiple targets by Multi-Bernoulli filtering of background subtracted image data |
| title_fullStr | Visual tracking of multiple targets by Multi-Bernoulli filtering of background subtracted image data |
| title_full_unstemmed | Visual tracking of multiple targets by Multi-Bernoulli filtering of background subtracted image data |
| title_short | Visual tracking of multiple targets by Multi-Bernoulli filtering of background subtracted image data |
| title_sort | visual tracking of multiple targets by multi-bernoulli filtering of background subtracted image data |
| topic | multi-Bernoulli multi-target tracking Bayesian estimation random finite sets visual tracking |
| url | http://hdl.handle.net/20.500.11937/45604 |