Abstract
In order to improve the accuracy of long jump in long jump, combined with computer vision image processing method to correct the long jump trajectory in long jump, an adaptive tracking method of long jump trajectory tracking image based on machine vision tracking detection is proposed, and the video point frame scanning method is used to collect the long jump trajectory tracking image. The image of long jump athletes is segmented by adaptive pixel fusion method, and the automatic tracking and recognition of long jumpers’ motion trajectory tracking image is carried out based on dynamic feature segmentation. The grey feature quantity of long jump trajectory tracking image is extracted, and the neighborhood distribution model of long jump in long jump is constructed. According to the dynamic evolution characteristic distribution of the long jump trajectory, the dynamic characteristics of the long jump trajectory are analyzed, and the image segmentation of the long jump track tracking is realized by combining the spatial neighborhood enhancement technology, and the adaptive tracking of the long jump trajectory in the long jump is realized according to the image segmentation results. The simulation results show that this method has high accuracy in adaptive tracking image of long jump athletes, and improves the accuracy of long jump in long jump.
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Liao, Yd., Huang, Q. (2020). Research on the Adaptive Tracking Method for the Tracking of the Track of the Long-Jump Athletes. In: Zhang, YD., Wang, SH., Liu, S. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-030-51100-5_20
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DOI: https://doi.org/10.1007/978-3-030-51100-5_20
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