Multitarget tracking (MTT) is a challenging task that aims at estimating the number of targets and their states from measurements provided by one or multiple sensors. Additional information, such as imperfect estimates of target classes provided by a classifier, can facilitate the target-measurement association and thus improve MTT performance. In this letter, we describe how a recently proposed MTT framework based on the sum-product algorithm can be extended to efficiently exploit class information. The effectiveness of the proposed approach is demonstrated by simulation results.

中文翻译：

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使用和积算法的分类辅助多目标跟踪

多目标跟踪 (MTT) 是一项具有挑战性的任务，旨在通过一个或多个传感器提供的测量来估计目标的数量及其状态。附加信息，例如分类器提供的目标类别的不完美估计，可以促进目标-测量关联，从而提高 MTT 性能。在这封信中，我们描述了最近提出的基于 sum-product 算法的 MTT 框架如何扩展以有效利用类信息。仿真结果证明了所提出方法的有效性。