Gait Identification using the 3D Protrusion Transform

The present paper presents a novel approach for gait identification using 3D data and Krawtchouk moments to generate the descriptor feature vectors. The gait sequence is captured by a stereoscopic camera and the resulting 2.5D data are processed to generate a 3D hull of the captured silhouette. The 3D Protrusion Transform is then proposed that generates a silhouette image containing protrusion information. Finally, the descriptor vector of the extended silhouette is calculated using the Krawtchouk moments. Experimental evaluation illustrates that the proposed scheme is highly efficient in identifying gait sequences when compared to state of the art approaches.