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相关实验视频

Updated: Jul 10, 2025

Comparison of Kinetic Characteristics of Footwork during Stroke in Table Tennis: Cross-Step and Chasse Step
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一项基于空间域信息的乒乓球着陆点检测算法研究.

Tao Ning1,2, Changcheng Wang1,2, Meng Fu1,2

  • 1State Ethnic Affairs Commission Key Laboratory of Big Data Applied Technology, Institute of Computer Science, Dalian Minzu University, Dalian, 116650, China.

Scientific reports
|November 24, 2023
PubMed
概括
此摘要是机器生成的。

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本研究引入了一种实时方法,用于使用空间信息检测乒乓球着陆点,从而减少对视觉设备的依赖. 这种方法实现了高精度和速度,即使是低率.

科学领域:

  • 计算机视觉 计算机视觉
  • 机器人技术 机器人技术 机器人技术
  • 运动分析 运动分析

背景情况:

  • 传统的计算机视觉用于检测乒乓球,由于严重依赖视觉设备和缓慢的处理速度,因此面临限制.
  • 现有的方法在动态环境中难以实现实时性能和准确性.

研究的目的:

  • 开发一种实时方法,使用空间域信息准确确定乒乓球着陆点.
  • 减少对专门视力采集设备的依赖,提高处理速度.

主要方法:

  • 动态颜色值以识别对象的中心体.
  • 目标区域值和欧几里德距离用于降低噪音和干扰.
  • 关键提取以优化视频处理.
  • 四差异斜率和多边形面积测定用于着陆点和面积检测.

主要成果:

  • 动态色彩值实现了每秒45.3 (fps) 的检测速度.
  • 关键框架提取在识别着陆点框架方面显示了超过93.3%的准确性.
  • 拟议的方法实现了78.5%的整体准确度,用于实时检测乒乓球落球点.

结论:

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  • 这种新的方法可以准确地实时检测乒乓球的着陆点.
  • 这种方法即使在低率视觉设备和现实世界条件下也有效.
  • 该方法为改善乒乓球分析和训练系统提供了可行的解决方案.