Gibbs Sampling of Measurement Partitions and Associations for Extended Multi-Target Tracking

被引：0
|
作者：
Honer, Jens [1 ]
Schmieder, Fabian [1 ]
机构：
[1] Valeo Schalter & Sensoren GmbH, Bietigheim Bissingen, Germany
来源：
2019 22ND INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION 2019) | 2019年
关键词：
multi-target tracking; extended target tracking; random finite set filters; BERNOULLI; DERIVATION; FILTER;
D O I：
10.23919/fusion43075.2019.9011272
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper we propose a novel approach to handle the extended target association problem in multi-target tracking for conjugate priors like the (delta-GLMB, LMB, PMBM and MBM. By introducing dependencies between partition cells we are able to employ a Gibbs sampler to simultaneously sample from partitions of the measurement set and association mappings. This formulation allows for a reduction of the approximation error as well as a more efficient implementation.
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页数：8
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