基于智能手机运动传感器的步态特征身份识别方法

Gait feature identification method based on motion sensor in smartphone

利用行为特征进行身份验证是生物识别的前沿技术。为优化基于步态特征的身份识别研究中对数据的处理并改进识别的方式,提出利用智能手机运动传感器数据提取步态特征用于身份识别的方法。首先,应用空间转换算法解决传感器坐标系漂移问题,使数据可以完整准确地刻画行为特征;然后,利用支持向量机(SVM)算法对用户切换所导致的步态特征变化进行分类识别。实验结果表明,经过欧拉角法处理后,所提方法识别准确率达到95.5%,在有效识别用户变换的同时降低了空间开销和实现难度。

The identification based on behavior features is a leading technology of biometric recognition. In order to optimize the process of data processing and the way of recognition in the existing studies of identification based on gait feature, a method of extracting gait features from the data of smart phone motion sensors for identification was proposed. Firstly, a spatial transformation algorithm was used to solve the problem of sensor coordinate system drift, making the data to describe the behavior features completely and accurately. Then, Support Vector Machine(SVM) algorithm was used to classify and identify gait features change caused by user transformation. The experimental results show that, the identification accuracy of the proposed method is 95.5%. It can be used to effectively identify user transformation with reduction of space cost and implementation difficulty.