基于SVM的人体运动状态检测

计算机科学 ›› 2013, Vol. 40 ›› Issue (Z6): 166-168.

基于SVM的人体运动状态检测

于雷,辛晓越,卢志泳,陈志鹏,刘宁

中山大学软件学院广州 510006;中山大学软件学院广州 510006;中山大学软件学院广州 510006;中山大学软件学院广州 510006;中山大学软件学院广州 510006

出版日期:2018-11-16 发布日期:2018-11-16
基金资助:
本文受中山大学实验室开放基金项目(KF201117),中央高校基本科研业务费,中山大学青年教师培育项目(2010.62000.316.1035)资助

SVM-based Method and System for Recognition of Human Movement

YU Lei,XIN Xiao-yue,LU Zhi-yong,CHEN Zhi-peng and LIU Ning

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： 针对人体运动状态监测中出现的设备要求苛刻、预测精准确较低等问题,采用了一种基于支持向量机(SVM)的人体运动状态检测方法。该方法通过移动终端设备中的传感器获取人体运动数据,并利用SVM对“小数据集”进行运动状态建模和预测,最终实现了低设备要求、高准确度的人体运动状态检测,并通过实验验证了其有效性。

关键词: 支持向量机(SVM),运动状态监测,移动设备

Abstract: We propose to use the sensors in mobile devices to recognize the state of users movement by small data set．We suggest a mechanism,based the support vector machine(SVM),to model and classify the movement of mobile clients．Since the mobile devices will handle different sensor data in use,we suggest two coordinate system for the data set,called device coordinate and the standard coordinate．After the sensor data in device coordinate being mapped to the standard coordinate,they will be put into support vector machine and produce classification results with high accuracy．A realistic study have been conducted to prove that the mechanism is practical and accurate．

Key words: Support vector machine,Motion state monitoring,Mobile devices

于雷,辛晓越,卢志泳,陈志鹏,刘宁. 基于SVM的人体运动状态检测[J]. 计算机科学, 2013, 40(Z6): 166-168. https://doi.org/

YU Lei,XIN Xiao-yue,LU Zhi-yong,CHEN Zhi-peng and LIU Ning. SVM-based Method and System for Recognition of Human Movement[J]. Computer Science, 2013, 40(Z6): 166-168. https://doi.org/

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