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dc.contributor.authorReuter, S.
dc.contributor.authorVo, Ba Tuong
dc.contributor.authorVo, Ba-Ngu
dc.contributor.authorDietmayer, K.
dc.contributor.editorJuan M. Corchado
dc.identifier.citationReuter, S. and Vo, B.T. and Vo, B. and Dietmayer, K. 2014. Multi-Object Tracking Using Labeled Multi-Bernoulli Random Finite Sets, in 17th International Conference on Information Fusion (FUSION), Jul 7 2014. Salamanca, Spain: IEEE.

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.

dc.titleMulti-Object Tracking Using Labeled Multi-Bernoulli Random Finite Sets
dc.typeConference Paper
dcterms.source.conference2014 17th International Conference on Information Fusion (FUSION)
dcterms.source.conference-start-dateJul 7 2014
dcterms.source.conferencelocationSalamanca, Spain
dcterms.source.placeNew Jersey, USA
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available

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