基于人工鱼群算法的篮球跳投轨迹实时跟踪  

Real-time track of basketball jump shot trajectory based on artificial fish swarm algorithm

作　　者：张龙[1] ZHANG Long(Sports Training College of Xi’an Physical Education University,Xi’an 710068,China)

机构地区：[1]西安体育学院运动训练学院,西安710068

出　　处：《信息技术》2024年第5期104-109,共6页Information Technology

基　　金：陕西省自然科学基金项目(61223503)。

摘　　要：篮球运动轨迹跟踪方法由于轨迹特征提取效果差,导致跟踪误差高,提出一种基于人工鱼群算法的篮球跳投轨迹实时跟踪方法。提取三维坐标系下图像中篮球边缘轮廓信息,通过滤波函数消除篮球跳投图像噪声,基于人工鱼群算法提取图像中篮球跳投轨迹特征,寻找篮球运动轨迹的最优解集,改进篮球实时跟踪匹配路径,形成轨迹跟踪函数。实验结果可知,该方法的平均轨迹跟踪误差为18.28mm,与常规方法相比降低了6.22mm以上。因此,该跟踪方法的篮球轨迹跟踪精度更高,并且实时跟踪轨迹与真实轨迹更吻合。Since the tracking error is high caused by poor tracking feature lifting effect of the basketball,a real-time tracking method of basketball jump shot trajectory based on artificial fish swarm algorithm is proposed.The basketball edge contour information is extracted from the image under the three-dimensional coordinate system,and the noise of the basketball jump shot image is eliminated through the filter function.Then,the characteristics of the basketball long-distance jump shot trajectory in the image is extract based on the artificial fish swarm algorithm to find the optimal solution set of the basketball motion trajectory and improve the real-time basketball tracking matching path.Finally,the trajectory tracking function is formed.The experiment results show that the average trajectory tracking error of this method is 18.28 mm,which is reduced by more than 6.22 mm compared with the conventional method.Therefore,the basketball trajectory tracking accuracy of this tracking method is higher,and the real-time tracking trajectory is more consistent with the real trajectory.

关 键 词：人工鱼群算法 篮球跳投 滤波函数 运动轨迹 实时跟踪 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]