Gait recognition based on the Fast Fourier Transform and SVM

Abstract

Gait recognition is a new type of biometric identification technology. In the preliminary study of biped robot with heterogeneous legs, we detect road information by classify of subject's gait data by measurement using gyroscope. Then we can make bionic leg's movement to follow artificial leg's movement perfectly. So gait recognition is a very important step in it. This paper adopted the Fast Fourier Transform to the feature selection of time-series sequence of measurement gait data, and reduces the characteristic number of the samples into two. Then we detected the situation of road by gait recognition of different gait data on the different roads based support vector machine. The experiment shows a good result, and the method reduces the computing time significantly.