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Parallelization of a Multipartite Graph Matching Algorithm for Tracking Multiple Football Players

机译:跟踪多个足球运动员的多部分图匹配算法的并行化

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This work describes the parallel methodology for a football tracking algorithm based on multipartite graphs using MPI and OpenMP. The proposed algorithm use a consumer-producer scheme to overlap the computing time of the two main procedures of the tracking algorithm: segmentation and tracking; as well a send-and-receive communication pattern to propagate the blob identities. We show how an hybrid system of data and task parallelization improves the execution time for 4K videos, achieving a speedup equal to 19.24 and a processing speed of 21.71 FPS with 128 threads.
机译:这项工作描述了基于MPI和OpenMP的基于多部分图的足球跟踪算法的并行方法。所提出的算法使用消费者-生产者方案来重叠跟踪算法的两个主要过程的计算时间:分段和跟踪;以及跟踪。以及用于传播斑点身份的发送和接收通信模式。我们展示了数据和任务并行化的混合系统如何改善4K视频的执行时间,实现了等于19.24的加速和128个线程的21.71 FPS的处理速度。

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