Pose Depth Volume extraction from RGB-D streams for frontal gait recognition

Abstract

We explore the applicability of Kinect RGB-D streams in recognizing gait patterns of individuals. Gait energy volume (GEV) is a recently proposed feature that performs gait recognition in frontal view using only depth image frames from Kinect. Since depth frames from Kinect are inherently noisy, corresponding silhouette shapes are inaccurate, often merging with the background. We register the depth and RGB frames from Kinect to obtain smooth silhouette shape along with depth information. A partial volume reconstruction of the frontal surface of each silhouette is done and a novel feature termed as Pose Depth Volume (PDV) is derived from this volumetric model. Recognition performance of the proposed approach has been tested on a data set captured using Microsoft Kinect in an indoor environment. Experimental results clearly demonstrate the effectiveness of the approach in comparison with other existing methods.