Pace independent mobile gait biometrics

Abstract

Accelerometers embedded in mobile devices have shown great potential for non-obtrusive gait biometrics by directly capturing a user's characteristic locomotion. Although gait analysis using these sensors has achieved highly accurate authentication and identification performance under controlled experimental settings, the robustness of such algorithms in the presence of assorted variations typical in real world scenarios remains a major challenge. In this paper, we propose a novel pace independent mobile gait biometrics algorithm that is insensitive to variability in walking speed. Our approach also exploits recent advances in invariant mobile gait representation to be independent of sensor rotation. Performance evaluations on a realistic mobile gait dataset containing 51 subjects confirm the merits of the proposed algorithm toward practical mobile gait authentication.