A generalized labeled multi-bernoulli filter with object spawning
dc.contributor.author | Bryant, D. | |
dc.contributor.author | Vo, Ba Tuong | |
dc.contributor.author | Vo, Ba-Ngu | |
dc.contributor.author | Jones, B. | |
dc.date.accessioned | 2018-12-13T09:13:22Z | |
dc.date.available | 2018-12-13T09:13:22Z | |
dc.date.created | 2018-12-12T02:46:41Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Bryant, D. and Vo, B.T. and Vo, B. and Jones, B. 2018. A generalized labeled multi-bernoulli filter with object spawning. IEEE Transactions on Signal Processing. 66 (23): pp. 6177-6189. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/72442 | |
dc.identifier.doi | 10.1109/TSP.2018.2872856 | |
dc.description.abstract |
Previous labeled random finite set filter developments use a motion model that only accounts for survival and birth. While such a model provides the means for a multi-object tracking filter, such as the generalized labeled multi-Bernoulli (GLMB) filter to capture object births and deaths in a wide variety of applications, it lacks the capability to capture spawned tracks and their lineages. In this paper, we propose a new Generalized Labeled Multi-Bernoulli (GLMB)-based filter that formally incorporates spawning, in addition to birth. This formulation enables the joint estimation of a spawned object's state and information regarding its lineage. Simulations results demonstrate the efficacy of the proposed formulation. | |
dc.publisher | IEEE | |
dc.relation.sponsoredby | http://purl.org/au-research/grants/arc/DP170104854 | |
dc.relation.sponsoredby | http://purl.org/au-research/grants/arc/DP160104662 | |
dc.title | A generalized labeled multi-bernoulli filter with object spawning | |
dc.type | Journal Article | |
dcterms.source.volume | 66 | |
dcterms.source.number | 23 | |
dcterms.source.startPage | 6177 | |
dcterms.source.endPage | 6189 | |
dcterms.source.issn | 1053-587X | |
dcterms.source.title | IEEE Transactions on Signal Processing | |
curtin.department | School of Electrical Engineering, Computing and Mathematical Science (EECMS) | |
curtin.accessStatus | Fulltext not available |
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