Gait recognition using Hough transform and principal component analysis

In this paper, we propose a new spatio-temporal representation for gait recognition. Firstly, the new representation of gait is constructed, which is the average of the Hough transformed images in one complete cycle of a silhouette sequence. Secondly, we project the new representation to low dimension by applying Principal Component Analysis. Finally, the nearest neighbor rule is adopted for recognition. The results of experiments conducted on CASIA-A Gait Database show that the proposed gait recognition approach can obtain encouraging accurate recognition rates.