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Basketball Image Trajectory Analysis Based on Intelligent Acquisition of Mobile Terminal

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Abstract

In view of the obvious deviation of traditional methods in the analysis of basketball flight state, a basketball trajectory analysis method based on intelligent image of mobile terminal is designed. Firstly, the mobile terminal network equipment is used to effectively collect the basketball trajectory. The gray pixel set of basketball image is obtained. Combined with the nonlinear transformation method, the color of basketball image is enhanced and the image quality is effectively improved. Based on this, the running process of basketball is analyzed from two aspects of initial angle and initial running speed. High quality basketball trajectory image can ensure the accuracy of initial angle and initial running speed analysis. The experimental results show that the MAE value of this method is always lower than 0.1, the F-measure value is relatively high, and the duration of trajectory analysis is between 0.72 s and 0.81 s, which fully proves the effectiveness and feasibility of this method.

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Authors and Affiliations

  1. College of Education and Sports Sciences, Yangtze University, Jing Zhou, 434020, China

    Bin Yang

  2. Huali College Guangdong University of Technology, Guangzhou, 511325, China

    Jian-li Zhai

  3. Department of Industrial Security, Chung-Ang University, Seoul, 06974, Korea

    Seungmin Rho

Authors
  1. Bin Yang
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  2. Jian-li Zhai
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  3. Seungmin Rho
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Corresponding author

Correspondence to Seungmin Rho.

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Conflict of Interest

The authors have no relevant financial or non-financial interests to disclose. Bin Yang provided the algorithm and experimental results, Bin Yang and Jian-li Zhai wrote the manuscript, Seungmin Rho revised the paper, supervised and analyzed the experiment. We also declare that data availability and ethics approval is not applicable in this paper.

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Yang, B., Zhai, Jl. & Rho, S. Basketball Image Trajectory Analysis Based on Intelligent Acquisition of Mobile Terminal. Mobile Netw Appl 27, 2534–2542 (2022). https://doi.org/10.1007/s11036-022-02071-w

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