The Use of Dynamic and Static Characteristics of Gait for Individual Identification

Recently, gait recognition for individual identification has received much increased attention from biometrics researchers as gait can be captured at a distance by using low-resolution capturing device. Human gait properties can be affected by various contexts such as different clothing and carrying objects. Most of the literature shows that these clothing and carrying objects (i.e. covariate factors) give difficulties for gait recognition. In this paper, we propose a novel method that generates dynamic and static feature templates of the sequences of silhouette images called Dynamic Static Silhouette Templates (DSSTs) to overcome this issue. Here the DSST is calculated from Gait Energy Images (GEIs). DSSTs capture the dynamic and static characteristics of gait. The experimental results show that our method overcomes the issues arising from differing clothing and the carrying of objects.