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Polynomial time algorithm for data association problem in multitarget tracking

机译:多目标跟踪中数据关联问题的多项式时间算法

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The aim of this work is to propose a semigreedy algorithm for solving the data association problem (DAP) arising in multitarget tracking. The DAP is characterized as a maximum weighted set partitioning problem (MWSPP). A semigreedy algorithm that first generates a number of different solutions using a polynomial number of operations and then selects the best among the solutions generated is presented. Theoretically we prove that the value of the solution returned by the algorithm approximates the value of the optimal solution within a guaranteed factor. This factor only depends on the dimension of the sliding window used. Computational experiments indicate that the quality of the solutions returned is quite satisfactory.
机译:这项工作的目的是提出一种半贪婪算法,用于解决多目标跟踪中出现的数据关联问题(DAP)。 DAP的特征是最大加权集划分问题(MWSPP)。提出了一种半贪婪算法,该算法首先使用多项式运算来生成多个不同的解,然后在生成的解中选择最佳。从理论上讲,我们证明了算法返回的解的值在保证因子内近似于最优解的值。该因素仅取决于所使用的滑动窗的尺寸。计算实验表明,返回的溶液质量相当令人满意。

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