Realtime Person Identification via Gait Analysis

arXiv:2404.15312v1 Announce Type: cross
Abstract: Each person has a unique gait, i.e., walking style, that can be used as a biometric for personal identification. Recent works have demonstrated effective gait recognition using deep neural networks, however most of these works predominantly focus on classification accuracy rather than model efficiency. In order to perform gait recognition using wearable devices on the edge, it is imperative to develop highly efficient low-power models that can be deployed on to small form-factor devices such …

abstract accuracy analysis arxiv biometric classification cs.cv eess.sp efficiency focus however identification networks neural networks person realtime recognition style type unique via walking