摘要
为了提高篮球运动员远距离投篮轨迹跟踪识别能力,提出基于蚁群算法的轨迹跟踪识别方法。采用动力传感敏感跟踪元件实现投篮轨迹数据采集,构建篮球运动员远距离投篮轨迹数据特征分析模型;结合运动学参数融合和动态识别方法进行远距离投篮轨迹数据的分类检测,构建远距离投篮轨迹的运动力学耦合控制模型;采用蚁群个体寻优跟踪方法,构建篮球运动员远距离投篮轨迹数据的聚类参数演化分布集;通过动力传感敏感跟踪元件融合方法,进行篮球运动员远距离投篮轨迹数据感知过程中的自适应学习,构建篮球运动员远距离投篮轨迹分布的信息融合模型;通过级联滤波和联合特征分析方法,实现对篮球运动员远距离投篮轨迹跟踪和特征识别;通过蚁群寻优结果,实现对篮球运动员远距离投篮轨迹信息跟踪识别。仿真结果表明:采用该方法实现篮球运动员远距离投篮轨迹跟踪识别的精度较高,误差较小。
In order to improve basketball players′ ability of tracking and identifying long-distance shooting trajectory,a method of tracking and identifying basketball players′ long-distance shooting trajectory based on ant colony algorithm is proposed.In this tracking method,we adopt dynamic sensing sensitive tracking elements to collect data of basketball players′ long-distance shooting trajectory and construct a characteristic analysis model of basketball players′ long-distance shooting trajectory data;classify and detect basketball players′ long-distance shooting trajectory data by combining kinematic parameter fusion and dynamic recognition methods to construct a kinematic mechanics coupling control model of basketball players′ long-distance shooting trajectory;adopt the ant colony individual optimization tracking method to construct the cluster parameter evolution distribution set of basketball players′ long-distance shooting trajectory data;adopt the fusion method of dynamic sensing sensitive tracking elements to carry out the adaptive learning of basketball players′ longdistance shooting trajectory data sensing process;use cascade filtering and joint feature analysis methods to conduct the long-distance shooting trajectory tracking and feature recognition of basketball players;track and identify the information of basketball players′ long-distance shooting trajectory through the results of ant colony optimization algorithms. The simulation results show this method has high accuracy and slight deviations in tracking and identifying basketball players′long-distance shooting trajectory.
作者
程翔
张燕中
CHENG Xiang;ZHANG Yanzhong(Sports Department,Tongling University,Tongling,Anhui 244000,China;Sports Department,Anhui Agricultural University,Hefei,Anhui 230036,China)
出处
《西昌学院学报(自然科学版)》
2021年第4期93-97,共5页
Journal of Xichang University(Natural Science Edition)
基金
安徽省教育厅教学研究重点项目(2019jyxm0105)。
关键词
蚁群算法
篮球
运动员
远距离投篮
轨迹跟踪
ant colony optimization algorithms
basketball
athletes
long-distance shooting
trajectory tracking