Canonical View Synthesis for Gait Recognition

GAIT is defined as a person´s manner of walking. While the computer vision community has progressed the identification of individuals by means of their gait, there are many difficulties which are not settled yet. Especially, dependency to the direction of walking is very serious. That is, extracted gait features become individualized according to the direction of walking, even if the camera is fixed. In this paper we propose an improvement to reduce this dependency based on homography. We establish a direction of walking through the silhouette of gait then estimate the planar homography by means of simple operations. Through transformation using planar homography we reduce dependency to the direction of the gait features. In order to estimate planar homography, vanishing point and vanishing lines are considered. The proposed planar homography that transforms the vanishing point to infinity makes the corresponding directional vanishing lines parallel, and this can always transform any plane that is established by the integrated silhouette of gait to the canonical plane. Therefore one can obtain the canonical-viewed images using the estimated homography. Moreover, through synthesizing of canonical-viewed images by means of the estimated homography, a viewpoint variation from the direction of walking is compensated. To test this idea we segment the gait silhouette into sub-regions and use the averaged features and variations on each region, as input to a gait recognition experiment. Our experiments show that the proposed method efficiently reduces the dependency to directional variations of gait.