Gait recognition based on modified phase only correlation

Abstract

Clothing, carrying conditions, and other intra-class variations, also referred as "covariates", affect the performance of gait recognition systems. This paper proposes a supervised feature extraction method which is able to select relevant features for human recognition to mitigates the impact of covariates and hence improve the recognition performance. The proposed method is evaluated using CASIA Gait Database (Dataset B) and the experimental results suggest that our method yields attractive results. © 2014 Springer International Publishing.