2020/01/23 by Srđan Kitić, Gilles Puy, Kitić, Srđan +5
Computer Science · Engineering · #Anomaly Detection Techniques and Applications #Audio and Speech Processing (eess.AS) #FOS: Computer and information sciences #FOS: Electrical engineering #Gait Recognition and Analysis #Machine Learning (cs.LG) #Signal Processing (eess.SP) #Sound (cs.SD) #Video Surveillance and Tracking Methods #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2001.08830
openalex publication_date 2020/01/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We consider the problem of identifying people on the basis of their walk (gait) pattern. Classical approaches to tackle this problem are based on, e.g., video recordings or piezoelectric sensors embedded in the floor. In this work, we rely on acoustic and vibration measurements, obtained from a microphone and a geophone sensor, respectively. The contribution of this work is twofold. First, we propose a feature extraction method based on an (untrained) shallow scattering network, specially tailored for the gait signals. Second, we demonstrate that fusing the two modalities improves identification in the practically relevant open set scenario.