Multi-Object Tracking Using Labeled Multi-Bernoulli Random Finite Sets
In this paper, we propose the labeled multi-Bernoulli filter which explicitly estimates target tracks and provides a more accurate approximation of the multi-object Bayes update than the multi-Bernoulli filter. In particular, the labeled multi-Bernoulli filter is not prone to the biased cardinality...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
IEEE
2014
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| Online Access: | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6916141 http://hdl.handle.net/20.500.11937/42972 |
| _version_ | 1848756562437341184 |
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| author | Reuter, S. Vo, Ba Tuong Vo, Ba-Ngu Dietmayer, K. |
| author2 | Juan M. Corchado |
| author_facet | Juan M. Corchado Reuter, S. Vo, Ba Tuong Vo, Ba-Ngu Dietmayer, K. |
| author_sort | Reuter, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In this paper, we propose the labeled multi-Bernoulli filter which explicitly estimates target tracks and provides a more accurate approximation of the multi-object Bayes update than the multi-Bernoulli filter. In particular, the labeled multi-Bernoulli filter is not prone to the biased cardinality estimate of the multi-Bernoulli filter. The utilization of the class of labeled random finite sets naturally incorporates the estimation of a targets identity or label. Compared to the d-generalized labeled multi-Bernoulli filter, the labeled multi-Bernoulli filter is anefficient approximation which obtains almost the same accuracy at significantly lower computational cost. The performance of thelabeled multi-Bernoulli filter is compared to the multi-Bernoulli filter using simulated data. Further, the real-time capability of the filter is illustrated using real-world sensor data of our experimental vehicle. |
| first_indexed | 2025-11-14T09:14:10Z |
| format | Conference Paper |
| id | curtin-20.500.11937-42972 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:14:10Z |
| publishDate | 2014 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-429722017-01-30T15:03:33Z Multi-Object Tracking Using Labeled Multi-Bernoulli Random Finite Sets Reuter, S. Vo, Ba Tuong Vo, Ba-Ngu Dietmayer, K. Juan M. Corchado In this paper, we propose the labeled multi-Bernoulli filter which explicitly estimates target tracks and provides a more accurate approximation of the multi-object Bayes update than the multi-Bernoulli filter. In particular, the labeled multi-Bernoulli filter is not prone to the biased cardinality estimate of the multi-Bernoulli filter. The utilization of the class of labeled random finite sets naturally incorporates the estimation of a targets identity or label. Compared to the d-generalized labeled multi-Bernoulli filter, the labeled multi-Bernoulli filter is anefficient approximation which obtains almost the same accuracy at significantly lower computational cost. The performance of thelabeled multi-Bernoulli filter is compared to the multi-Bernoulli filter using simulated data. Further, the real-time capability of the filter is illustrated using real-world sensor data of our experimental vehicle. 2014 Conference Paper http://hdl.handle.net/20.500.11937/42972 http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6916141 IEEE restricted |
| spellingShingle | Reuter, S. Vo, Ba Tuong Vo, Ba-Ngu Dietmayer, K. Multi-Object Tracking Using Labeled Multi-Bernoulli Random Finite Sets |
| title | Multi-Object Tracking Using Labeled Multi-Bernoulli Random Finite Sets |
| title_full | Multi-Object Tracking Using Labeled Multi-Bernoulli Random Finite Sets |
| title_fullStr | Multi-Object Tracking Using Labeled Multi-Bernoulli Random Finite Sets |
| title_full_unstemmed | Multi-Object Tracking Using Labeled Multi-Bernoulli Random Finite Sets |
| title_short | Multi-Object Tracking Using Labeled Multi-Bernoulli Random Finite Sets |
| title_sort | multi-object tracking using labeled multi-bernoulli random finite sets |
| url | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6916141 http://hdl.handle.net/20.500.11937/42972 |