摘要
文章提出了一种基于SVM支持向量机分类器的数据挖掘方法,设计实现了一种基于智能手表加速度传感器的人体行为识别系统。该系统通过对对象移动过程中的加速度感知信号进行处理和数据挖掘,动态识别移动对象的运动行为模式,并实验验证了其准确率和有效性。实验证明,基于SVM算法的分类器对四种人体行为有着较高的识别准确率。
The paper puts forward to a data-mining method based on the SVM classifier, designing and implementing a human-body behavior recognition system based on the accelerator sensor of smartwatch.the system dynamically identifies the movement behavior pattems of moving objects through the process of accelerator sensing signal processing and data mining, and verify the accuracy and effectiveness by experiment. It proves that the classifier based on the SVM algorithm has a high recognition rate focusing on the four human behavior.
出处
《电脑与信息技术》
2015年第5期6-8,33,共4页
Computer and Information Technology
关键词
智能手表
支持向量机
行为识别
intelligent watch
support vector machine
behavior recognition
