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

dc.creatorVillalta Fallas, Marco
dc.creatorSiles Canales, Francisco
dc.date.accessioned2020-05-28T20:12:24Z
dc.date.accessioned2022-10-19T23:48:34Z
dc.date.available2020-05-28T20:12:24Z
dc.date.available2022-10-19T23:48:34Z
dc.date.created2020-05-28T20:12:24Z
dc.date.issued2018
dc.identifierhttps://ieeexplore.ieee.org/document/8745720
dc.identifierhttps://hdl.handle.net/10669/81102
dc.identifier10.1109/PDGC.2018.8745720
dc.identifier838-B6-751
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4524151
dc.description.abstractThis 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.
dc.languageen_US
dc.source2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC)
dc.subjecttemporal segmentation
dc.subjectparallel algorithms
dc.subjecttracking of football players
dc.subjectassociation footbal
dc.titleParallelization of a Multipartite Graph Matching Algorithm for Tracking Multiple Football Players
dc.typecontribución de congreso


Este ítem pertenece a la siguiente institución