Abstract
Aiming at the problems of large tracking error and long tracking time in traditional multiperson target dynamic tracking methods, a new method based on wireless body area network for athlete training multiperson target dynamic tracking is proposed. First, the microinertial sensor in the wireless body area network is used to collect the multiperson image data of the athlete training, and the sparse representation is performed after processing, which improves the reliability of the data and reduces the tracking error. Secondly, the multiperson target dynamic tracking method based on the adaptive search box is used, combined with target isolation and occlusion detection, to judge the athlete’s training target. Finally, the nearest neighbor algorithm is used to construct an adaptive search box to achieve dynamic tracking of multiple targets. Experimental results show that this method can accurately measure the similarity of target features, with small tracking error and short tracking time. The minimum tracking error is only 0.11 frame.
Highlights
In modern life, sports competitions have been deeply loved by the majority of the audience
(2) The microinertial sensor in the wireless body area network is used to collect the multiperson image data of the athlete’s training, and the sparse representation is performed after processing, which improves the reliability of the data and reduces the tracking error
In order to verify the proposed multiperson target dynamic tracking method for athlete training based on wireless body area network, simulation and comparative verification experiments are carried out
Summary
Sports competitions have been deeply loved by the majority of the audience. In view of the poor effect of the existing multiperson target detection and tracking methods in the dynamic scene, taking the dynamic tracking of athlete training as the research object, based on the existing research theory, the multiperson images of athlete training are accurately collected by wireless body area network, and the collected images are sparse represented. 2. Multiperson Target Dynamic Tracking of Athlete Training Based on Wireless Body Area Network. Its essential content is to first obtain the motion signal generated during athlete training through one or more inertial sensors and sparse represent the sampled image, so as to facilitate the follow-up athlete training multiperson target dynamic tracking [12]. The multitarget motion data is collected according to the microinertial sensor in the wireless body area network, which lays the foundation for the subsequent multitarget dynamic tracking of multiplayer training.
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