Original scientific paper

https://doi.org/10.17559/TV-20250411002583

Research on Object Detection and Tracking in Sports Competitions using Two-Dimensional Fuzzy Semantic Algorithm

Linlin Wang orcid.org/0000-0002-6823-7245 ; School of Physical Education, Zhoukou Normal University, Zhoukou 466001, Henan, China *

* Corresponding author.

Abstract

The research object of this paper is the sports game video. The athlete's motion state is clearly displayed in the video, and the target detection and tracking for the specified athlete is realized. A T-S fuzzy semantic interactive maneuvering target tracking algorithm based on two-dimensional fuzzy semantic reduction is proposed. Firstly, a knowledge system is composed of the weights of each model and the parameters of the previous ones, and the redundant models are eliminated by neighborhood fuzzy intensive reduction. At the same time, excessive fuzzy intensive reduction will consume a lot of computing power and lose effective information. An adaptive reduction judgment algorithm is proposed according to each moment and each model residual. Through residual monitoring and tracking, feature re-reduction and feature re-reduction can be adaptive. The experimental results show that the 2D fuzzy semantics can effectively reduce the features and improve the real-time performance of the algorithm. The test results show that the proposed method can effectively improve false alarm rate and tracking accuracy, and has higher robustness than traditional target detection and tracking in real complex competition venues.

Keywords

interactive maneuvering target tracking; reduction judgment algorithm; sports competitions; target detection and tracking; two-dimensional fuzzy semantic algorithm

Hrčak ID:

335077

URI

https://hrcak.srce.hr/335077

Publication date:

30.8.2025.

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