摘要
为了能够有效地提取人体行为特征,提出了一种基于加速度传感器的人体行为识别系统,主要识别站立、行走、跑步、上楼、下楼这5种人体行为。该系统通过提取标准差、偏度、峰度和相关系数等统计特征来实现多层分类。实验表明,该系统可以有效地对这5种人体行为进行识别。
In order to extract the characteristics of human behavior effectively, this paper proposes a system for activity recognition based on a tri-axis accelerometer. Five activity such as standing, walking, running, up stair and down stair are recognized in this system. Many Statistical characteristics are proposed including standard deviation, skewness, kurtosis and correlation coefficient for classification. Experiments show that, the system can effectively identify the five kinds of human behavior.
出处
《电脑开发与应用》
2014年第12期55-57,共3页
Computer Development & Applications
关键词
加速度传感器
行为识别
特征提取
acceleration sensor
activity recognition
feature extraction