A Structural Vibration-based Dataset for Human Gait Recognition.

ABSTRACT: We present a dataset designed to advance non-intrusive human gait recognition using structural vibration. Structural vibrations, resulting from the rhythmic impacts of toes and heels on the ground, offer a unique, privacy-preserving gait recognition modality. We curated the largest dataset consisting of structural vibration signals from 100 subjects. Existing datasets in this domain are limited in scope, typically involving around ten participants and offering minimal exploration. To comprehensively investigate this modality, we recorded vibration signals across three distinct floor types-wooden, carpet, and cement-and at three different distances from a geophone sensor (1.5 m, 2.5 m, and 4.0 m), involving 40 and 30 participants, respectively. The dataset also includes video recordings of

SUBMITTER: Chakraborty M 

PROVIDER: S-EPMC12501299 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature