Multi-Bernoulli based track-before-detect with road constraints
The random set based multi-Bernoulli filter is applied to a challenging low signal to noise track before detect scenario. Specifically we use the variant of the multi-Bernoulli filter that processes raw image observations. We add an additional layer of track management logic to output trajectories r...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
IEEE
2012
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| Online Access: | http://hdl.handle.net/20.500.11937/35786 |
| _version_ | 1848754590978146304 |
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| author | Wong, J. Vo, Ba Tuong Vo, Ba-Ngu Hoseinnezhad, R. |
| author2 | Gee Wah NG |
| author_facet | Gee Wah NG Wong, J. Vo, Ba Tuong Vo, Ba-Ngu Hoseinnezhad, R. |
| author_sort | Wong, J. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The random set based multi-Bernoulli filter is applied to a challenging low signal to noise track before detect scenario. Specifically we use the variant of the multi-Bernoulli filter that processes raw image observations. We add an additional layer of track management logic to output trajectories rather than point estimates. The tracker also exploits additional road map information by integrating the roads into the filtering likelihood. We show that this approach of using the image observation MeMBer filter with track management and road constrained model can yield an effective tracker for track before detect scenarios. |
| first_indexed | 2025-11-14T08:42:50Z |
| format | Conference Paper |
| id | curtin-20.500.11937-35786 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:42:50Z |
| publishDate | 2012 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-357862017-01-30T13:51:44Z Multi-Bernoulli based track-before-detect with road constraints Wong, J. Vo, Ba Tuong Vo, Ba-Ngu Hoseinnezhad, R. Gee Wah NG The random set based multi-Bernoulli filter is applied to a challenging low signal to noise track before detect scenario. Specifically we use the variant of the multi-Bernoulli filter that processes raw image observations. We add an additional layer of track management logic to output trajectories rather than point estimates. The tracker also exploits additional road map information by integrating the roads into the filtering likelihood. We show that this approach of using the image observation MeMBer filter with track management and road constrained model can yield an effective tracker for track before detect scenarios. 2012 Conference Paper http://hdl.handle.net/20.500.11937/35786 IEEE restricted |
| spellingShingle | Wong, J. Vo, Ba Tuong Vo, Ba-Ngu Hoseinnezhad, R. Multi-Bernoulli based track-before-detect with road constraints |
| title | Multi-Bernoulli based track-before-detect with road constraints |
| title_full | Multi-Bernoulli based track-before-detect with road constraints |
| title_fullStr | Multi-Bernoulli based track-before-detect with road constraints |
| title_full_unstemmed | Multi-Bernoulli based track-before-detect with road constraints |
| title_short | Multi-Bernoulli based track-before-detect with road constraints |
| title_sort | multi-bernoulli based track-before-detect with road constraints |
| url | http://hdl.handle.net/20.500.11937/35786 |