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使用最短路径快速关联算法的多目标跟踪

Multiple object tracking using the shortest path faster association algorithm.

作者信息

Xi Zhenghao, Liu Heping, Liu Huaping, Yang Bin

机构信息

School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China ; State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing 100084, China.

School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China.

出版信息

ScientificWorldJournal. 2014;2014:481719. doi: 10.1155/2014/481719. Epub 2014 Aug 17.

DOI:10.1155/2014/481719
PMID:25215322
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4151586/
Abstract

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time.

摘要

为解决复杂环境下的持续多目标跟踪问题，本文提出了一种基于最短路径快速算法的新型跟踪关联方法。首先，将多目标跟踪问题表述为流网络的整数规划问题。然后，将整数规划松弛为标准线性规划问题。因此，利用最短路径快速算法可快速获得全局最优解。该方法避免了整数规划的困难，与竞争方法相比，其最坏情况复杂度更低，但在复杂环境下具有更好的鲁棒性和跟踪精度。仿真结果表明，该算法比其他现有方法耗时更少，能够实时运行。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1435/4151586/e2a27e92584a/TSWJ2014-481719.013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1435/4151586/b7a0fcb40b81/TSWJ2014-481719.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1435/4151586/48f224b96877/TSWJ2014-481719.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1435/4151586/266cf6ab20fd/TSWJ2014-481719.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1435/4151586/09c03482b346/TSWJ2014-481719.010.jpg
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