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arXiv · 1804.06622

A Solution for Large-scale Multi-object Tracking

Michael Beard·Ba Tuong Vo·Ba-Ngu Vo
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Abstract

A large-scale multi-object tracker based on the generalised labeled multi-Bernoulli (GLMB) filter is proposed. The algorithm is capable of tracking a very large, unknown and time-varying number of objects simultaneously, in the presence of a high number of false alarms, as well as misdetections and measurement origin uncertainty due to closely spaced objects. The algorithm is demonstrated on a simulated large-scale tracking scenario, where the peak number objects appearing simultaneously exceeds one million. To evaluate the performance of the proposed tracker, we also introduce a new method of applying the optimal sub-pattern assignment (OSPA) metric, and an efficient strategy for its evaluation in large-scale scenarios.

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Michael Beard, Ba Tuong Vo, Ba-Ngu Vo. 2018-04-18. A Solution for Large-scale Multi-object Tracking. https://arxiv.org/abs/1804.06622

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