Gait-ID on the move: Pace independent human identification using cell phone accelerometer dynamics

Abstract

In this paper, we have proposed a robust, acceleration based, pace independent gait recognition framework using Android smartphones. From our extensive experiments using cyclostationarity and continuous wavelet transform spectrogram analysis on our gait acceleration database with both normal and fast paced data, our proposed algorithm has outperformed the state-of-the-art by a great margin. To be more specific, for normal to normal pace matching, we are able to achieve 99.4% verification rate (VR) at 0.1% false accept rate (FAR); for fast vs. fast, we are able to achieve 96.8% VR at 0.1% FAR; for the challenging normal vs. fast, we are still able to achieve 61.1% VR at 0.1% FAR. The findings have laid the foundation of pace independent gait recognition using mobile devices with high accuracy.