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arXiv · 2110.11954

Variational Probabilistic Multi-Hypothesis Tracking

Shuoyuan Xu·Hyo-Sang Shin·Antonios Tsourdos
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Abstract

This paper proposes a novel multi-target tracking (MTT) algorithm for scenarios with arbitrary numbers of measurements per target. We propose the variational probabilistic multi-hypothesis tracking (VPMHT) algorithm based on the variational Bayesian expectation-maximisation (VBEM) algorithm to resolve the MTT problem in the classic PMHT algorithm. With the introduction of variational inference, the proposed VPMHT handles track-loss much better than the conventional probabilistic multi-hypothesis tracking (PMHT) while preserving a similar or even better tracking accuracy. Extensive numerical simulations are conducted to demonstrate the effectiveness of the proposed algorithm.

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BibTeXRIS

Shuoyuan Xu, Hyo-Sang Shin, Antonios Tsourdos. 2021-10-25. Variational Probabilistic Multi-Hypothesis Tracking. https://arxiv.org/abs/2110.11954

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