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吉林化工学院学报, 2021, 38(5): 32-37     https://doi.org/10.16039/j.cnki.cn22-1249.2021.05.007
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基于KNN算法的跑步运动轨迹监测系统设计
吴博
浙江旅游职业学院 公共教学部,浙江 杭州  311200
Design of running track monitoring system based on KNN algorithm
WU Bo
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摘要 

针对传统的跑步运动轨迹监测系统容易受到环境影响,导致监测结果准确性差的问题,提出基于KNN算法的跑步运动轨迹监测系统设计。利用射频子模块捕捉IMX179型号摄像头拍摄到的图像,控制子模块处理图像数据,并通过PCI总线传输信息。采用上下位机模块处理轨迹信息,通过指示灯显示跟踪结果。利用KNN算法识别跑步运动姿态,构建跑步运动方程。实验结果表明,该系统正面和背面两个角度下的跑步运动轨迹监测最大误差在可接受范围内,监测结果具有较高准确性。

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吴博
关键词:  KNN算法  跑步运动  运动轨迹  监测系统     
Abstract: 

Aiming at the problem that the traditional running track monitoring system is easily affected by the environment, which leads to the poor accuracy of monitoring results, this paper proposes the design of running track monitoring system based on KNN algorithm. This study uses the RF sub module to capture the image captured by imx179 camera, control the sub module to process the image data, and transmit information through PCI bus, uses control sub module to process the image data and transmits information through PCI bus. In addition, the module of upper and lower computer is used to process track information, and the tracking results are displayed by indicator light, and KNN algorithm is used to recognize running posture and build running equation. The experimental results show that the maximum error of running trajectory monitoring in the front and back angles of the system is within the acceptable range, and the monitoring results have high accuracy.

Key words:  KNN algorithm    Running    path of particle    Monitoring system
               出版日期:  2021-05-25      发布日期:  2021-05-25      整期出版日期:  2021-05-25
ZTFLH:  TP391.41  
引用本文:    
吴博. 基于KNN算法的跑步运动轨迹监测系统设计 [J]. 吉林化工学院学报, 2021, 38(5): 32-37.
WU Bo. Design of running track monitoring system based on KNN algorithm . Journal of Jilin Institute of Chemical Technology, 2021, 38(5): 32-37.
链接本文:  
http://xuebao.jlict.edu.cn/CN/10.16039/j.cnki.cn22-1249.2021.05.007  或          http://xuebao.jlict.edu.cn/CN/Y2021/V38/I5/32
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