Personal Authentication by Walking Motion using Kinect

Abstract

In recent years, with the rapid development of the information society, the importance of personal authentication has become higher and higher. This paper focuses on the use of a Kinect sensor to obtain walking characteristics for personal authentication. In terms of the proposal method, Kinect is used to obtain body's physical feature quantity, such as the angle of joint bending when a person walks, the displacement of coordinates. In terms of learning recognition, the support vector machine and the obtained feature amount are used for personal authentication. We measured 3 subjects data 5 times a day for 4 days, and obtained an average recognition accuracy of 77.4 % using cross-validation.