Depth-based Gait Authentication for Practical Sensor Settings

This paper investigates performances of silhouette-based and depth-based gait authentication considering practical sensor settings where sensors are located in an environments afterwards and usually have to be located quite near to people. To realize fair comparison between different sensors and methods, we construct full-body volume of walking people by a multi-camera environment so as to reconstruct virtual silhouette and depth images at arbitrary sensor positions. In addition, we also investigate performances when we have to authenticate between frontal and rear views. Experimental results confirm that the depth-based methods outperform the silhouette-based ones in the realistic situations. We also confirm that by introducing Depth-based Gait Feature, we can authenticate between the frontal and rear views.