Reducing the effect of noise on human contour in gait recognition

Abstract

Gait can be easily acquired at a distance, so it has become a popular biometric especially in intelligent visual surveillance. In gait-based human identification there are many factors that may degrade the performance, and noise on human contours is a significant one because to extract contours perfectly is a hard problem especially in a complex background. The contours extracted from video sequences are often polluted by noise. To improve the performance, we have to reduce the effect of noise. Different from the methods which use dynamic time warping (DTW) in previous work to match sequences in the time domain, a DTW-based contour similarity measure in the spatial domain is proposed to reduce the effect of noise. The experiments on a large gait database show the effectiveness of the proposed method. © Springer-Verlag Berlin Heidelberg 2007.