吉林大学学报(信息科学版) ›› 2026, Vol. 44 ›› Issue (2): 460-466.

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排球拦网扣球动作双臂末端轨迹实时跟踪算法设计

王 炜1 , 张振霖2   

  1. 1. 芜湖职业技术学院 体育教学部, 安徽 芜湖 241003; 2. 安徽工程大学 体育学院, 安徽 芜湖 241000
  • 收稿日期:2025-05-15 出版日期:2026-04-14 发布日期:2026-04-15
  • 作者简介:王炜(1977— ),男,安徽芜湖人, 芜湖职业技术学院副教授, 主要从事体育教学、运动训练研究, (Tel)86-13083217510(E-mail)ahwhww1977@163.com。
  • 基金资助:
    安徽省教育厅人文社科重点基金资助项目(2024AH053492); 芜湖职业技术学院校级质量工程基金资助项目(2022jxtd03)

Design of Real Time Tracking Algorithm for Double Arm End Trajectory of Volleyball Blocking and Spiking Action

WANG Wei 1 , ZHANG Zhenlin 2   

  1. 1. Sports Department, Wuhu Institute of Technology, Wuhu 241003, China;2. School of Physical Education, Anhui Polytechnic University, Wuhu 241000, China
  • Received:2025-05-15 Online:2026-04-14 Published:2026-04-15

摘要: 针对排球运动员在拦网扣球时, 上肢呈现湍流运动特征, 手臂末端速度产生类似刺水现象中入水涡环的非稳态流体轨迹, 导致难以捕捉排球运动员双臂末端位置, 跟踪末端位置误差较大的问题, 设计一种排球拦网扣球动作双臂末端轨迹实时跟踪算法。 利用边界区域信息重构方法, 确定动作视频中排球拦网扣球动作的起止帧。利用LM(Levenberg-Marquardt algorithm)算法, 将起止帧图像中的双臂末端骨骼点间的欧拉角作为优化变量, 捕捉排球运动员双臂末端位置。 基于双臂末端位置捕捉结果, 选取 Mean Shift 算法, 通过衡量双臂末端轨迹跟踪的目标模型与候选模型的相似性, 实时跟踪排球拦网扣球动作双臂末端轨迹。 实验结果表明, 该方法能精准跟踪排球拦网扣球动作的双臂末端轨迹, 末端位置误差低于 3 cm, 跟踪速度高于 30 f / s, 能满足高速运动环境下的排球动作分析需求。

关键词: 排球, 拦网扣球动作, 双臂末端, 轨迹实时跟踪, LM 算法, Mean Shift 算法

Abstract:

When volleyball players are blocking and spikling, their upper limbs show the characteristics of turbulent movement. The velocity at the end of the arms generates a non-steady-state fluid trajectory similar to the water vortex ring in the diving phenomenon, making it difficult to capture the position of the end of the volleyball players' arms and resulting in a large error in tracking the end position. To this end, a real-time tracking algorithm for the end trajectories of both arms in volleyball blocking and spikstroke actions is designed. By using the boundary area information reconstruction method, the start and end frames of the volleyball blocking spike action in the action video are determined. By using the LM(Levenberg-Marquardt algorithm) algorithm, the Euler Angle between the skeletal points at the ends of the arms in the start and end frame images is taken as the optimization variable to capture the positions at the ends of the arms of volleyball players. Based on the capture results of the end positions of both arms, the Mean Shift algorithm is selected. By measuring the similarity between the target model for tracking the end trajectories of both arms and the candidate models, the end trajectories of both arms for volleyball blocking spiks are tracked in real time. The experimental results show that this method can accurately track the end trajectories of both arms of the volleyball blocking spikstroke action. The end position error is less than 3 cm, and the tracking speed is higher than 30 f / s, which can meet the requirements of volleyball action analysis in a high-speed motion environment.

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中图分类号: 

  • TP391