Gait recognition based on marker-less 3D motion capture

Abstract

We present an algorithm for view-independent gait-based person identification. The identification is achieved using data obtained by our marker-less 3D motion tracking algorithm. The motion tracking was accomplished by a particle swarm optimization algorithm. The accuracy of the motion tracking algorithm was evaluated using ground-truth data from MoCap. It was determined on 88 sequences with 22 walking performers. We obtained 90% identification accuracy (rank 1) on 230 gait cycles.