Towards pose invariant gait reconstruction

Abstract

Recently, a lot of research has been conducted into the usefulness of gait for identification at a distance. Since the gait of a person is readily identified when extracted from a canonical side view, most algorithms work with the premise that the motion is frontoparallel in nature, or require some knowledge of the camera calibration. Realistically people always walk along different trajectories to the camera. In this paper we show that gait has sufficient properties that allows us to exploit the structure of articulated motion within single view sequences, in order to remove the unknown subject pose and reconstruct the underlying gait signature, with no prior knowledge of the camera calibration.