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Article Dans Une Revue IEEE Internet of Things Journal Année : 2020

WiDIGR: Direction-Independent Gait Recognition system using commercial Wi-Fi devices

Résumé

Gait recognition enables many potential applications requiring identification. Wi-Fi-based gait recognition is predominant because of its noninvasive and ubiquitous advantages. However, since the gait information changes with the walking direction, the existing Wi-Fi-based gait recognition systems require the subject to walk along a predetermined path. This direction dependence restriction impedes Wi-Fi-based gait recognition from being widely used. In order to address this issue, a direction-independent gait recognition system, called WiDIGR is proposed. WiDIGR can recognize a subject through the gait no matter what straight-line walking path it is. This relaxes the strict constraint of the other Wi-Fi-based gait recognition. Specifically, based on the Fresnel model, a series of signal processing techniques are proposed to eliminate the differences among induced signals caused by walking in different directions and generate a high-quality direction-independent signal spectrogram. Furthermore, effective features are extracted both manually and automatically from the direction-independent spectrogram. The experimental results in a typical indoor environment demonstrate the superior performance of WiDIGR, with mean accuracy ranging from 78.28% for a group of six subjects to 92.83% for a group of three.
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Dates et versions

hal-03002752 , version 1 (25-11-2020)

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Citer

Lei Zhang, Cong Wang, Maode Ma, Daqing Zhang. WiDIGR: Direction-Independent Gait Recognition system using commercial Wi-Fi devices. IEEE Internet of Things Journal, 2020, 7 (2), pp.1178 - 1191. ⟨10.1109/jiot.2019.2953488⟩. ⟨hal-03002752⟩
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