排球运动员手臂运动轨迹优化识别仿真研究

发布时间：2018-06-18 03:58

本文选题：排球运动员 + 运动轨迹　；参考：《计算机仿真》2017年02期

【摘要】：对于排球运动员手臂运动轨迹的优化研究可以有效提高运动员在比赛中扣球质量。进行挥臂动作轨迹的优化时需要进行动态手臂跟踪,将具有三维空间特征的运动轨迹转化为一维的运动轨迹。传统方法则忽略了该转化过程,直接对三维空间轨迹进行分析,导致轨迹优化过程复杂且优化效果不好。提出基于混沌理论的排球运动员手臂运动轨迹优化识别方法。以背景差分原理为依据检测运动员运动轨迹,利用颜色直方图的粒子滤波进行动态手臂跟踪,融合于混沌理论进行运动员手臂运动轨迹的相空间重构,从重构的相空间提取代表运动员手臂运动轨迹的混沌不变量,并将具有三维空间特征的手臂运动轨迹转化为一维的手臂运动轨迹,并完成了对排球运动员手臂运动轨迹优化识别。仿真结果表明,所提方法识别精确度高,为提升排球运动员扣球技术提供了有力的科学依据。
[Abstract]:The research on the optimal trajectory of volleyball players' arm movement can improve the quality of spiking effectively. In order to optimize the trajectory of swinging arm, the dynamic arm tracking is needed, and the three-dimension motion trajectory is transformed into one-dimensional motion track. The traditional method ignores the transformation process and analyzes the three-dimensional space trajectory directly, which leads to the complexity of the trajectory optimization process and the poor optimization effect. Based on chaos theory, an optimal identification method for the trajectory of volleyball players' arm motion is proposed. Based on the background difference principle, the athlete's motion trajectory is detected, and the dynamic arm tracking is carried out by using the particle filter of the color histogram, and the phase space reconstruction of the athlete's arm motion trajectory is carried out by integrating the chaos theory. The chaotic invariants representing the trajectory of the athlete's arm are extracted from the reconstructed phase space, and the three-dimension motion trajectory of the arm is transformed into the one-dimensional trajectory of the arm motion. And completed the volleyball player arm movement track optimization recognition. The simulation results show that the proposed method has high recognition accuracy and provides a powerful scientific basis for improving volleyball players' spiking technology.
【作者单位】：北京体育大学研究生院;成都体育学院;北京体育大学教育学院;
【分类号】：G842

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