Visual Tracking of Numerous Targets via Multi-Bernoulli Filtering of Image Data
This paper presents a novel Bayesian method to track multiple targets in an image sequence without explicit detection. Our method is formulated based on finite set representation of the multi-target state and the recently developed multi-Bernoulli filter. Experimental results on sport player and cel...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
Pergamon Press
2012
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| Online Access: | http://hdl.handle.net/20.500.11937/45836 |
| _version_ | 1848757395754319872 |
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| author | Hoseinnezhad, R. Vo, Ba-Ngu Vo, Ba Tuong Suter, D. |
| author_facet | Hoseinnezhad, R. Vo, Ba-Ngu Vo, Ba Tuong Suter, D. |
| author_sort | Hoseinnezhad, R. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This paper presents a novel Bayesian method to track multiple targets in an image sequence without explicit detection. Our method is formulated based on finite set representation of the multi-target state and the recently developed multi-Bernoulli filter. Experimental results on sport player and cell tracking studies show that our method can automatically track numerous targets, and it outperforms the state-of-the-art in terms of false positive (false alarm) and false negative (missing) rates as detection error measures, and in terms of label switching rate and lost tracks ratio as tracking error measures. |
| first_indexed | 2025-11-14T09:27:25Z |
| format | Journal Article |
| id | curtin-20.500.11937-45836 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:27:25Z |
| publishDate | 2012 |
| publisher | Pergamon Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-458362017-09-13T14:25:25Z Visual Tracking of Numerous Targets via Multi-Bernoulli Filtering of Image Data Hoseinnezhad, R. Vo, Ba-Ngu Vo, Ba Tuong Suter, D. This paper presents a novel Bayesian method to track multiple targets in an image sequence without explicit detection. Our method is formulated based on finite set representation of the multi-target state and the recently developed multi-Bernoulli filter. Experimental results on sport player and cell tracking studies show that our method can automatically track numerous targets, and it outperforms the state-of-the-art in terms of false positive (false alarm) and false negative (missing) rates as detection error measures, and in terms of label switching rate and lost tracks ratio as tracking error measures. 2012 Journal Article http://hdl.handle.net/20.500.11937/45836 10.1016/j.patcog.2012.04.004 Pergamon Press restricted |
| spellingShingle | Hoseinnezhad, R. Vo, Ba-Ngu Vo, Ba Tuong Suter, D. Visual Tracking of Numerous Targets via Multi-Bernoulli Filtering of Image Data |
| title | Visual Tracking of Numerous Targets via Multi-Bernoulli Filtering of Image Data |
| title_full | Visual Tracking of Numerous Targets via Multi-Bernoulli Filtering of Image Data |
| title_fullStr | Visual Tracking of Numerous Targets via Multi-Bernoulli Filtering of Image Data |
| title_full_unstemmed | Visual Tracking of Numerous Targets via Multi-Bernoulli Filtering of Image Data |
| title_short | Visual Tracking of Numerous Targets via Multi-Bernoulli Filtering of Image Data |
| title_sort | visual tracking of numerous targets via multi-bernoulli filtering of image data |
| url | http://hdl.handle.net/20.500.11937/45836 |