Affiliations: [a] School of Physical Education, Cangzhou Normal University, Cangzhou, Hebei, China
| [b] School of Continuing Education, Cangzhou Normal University, Cangzhou, Hebei, China
Correspondence:
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Corresponding author. Shoucun Zheng, School of Physical Education, Cangzhou Normal University, Cangzhou, Hebei, China. E-mail: [email protected].
Abstract: At present, there are efficiency problems in related algorithms for athlete detection and recognition. Based on this, this study analyzes the characteristics of athletes’ sports process. In this study, the Otsu method was used to perform grayscale feature processing. At the same time, based on the Harris corner extraction algorithm, this study proposes that the multi-target tracking combined with the corner feature of the target can be used to track different parts of the athlete as different target areas. In addition, this study uses a sequential algorithm to perform connected component labeling. Finally, in order to test the performance and recognition efficiency of the proposed algorithm, the performance of the algorithm is explored through experimental analysis. The research shows that the algorithm has good performance and has certain practical effects, and it has certain reference significance for subsequent related research.
Keywords: Visual image, sports, athlete, motion detection, skeletal model
