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.