Deep Adaptation Networks Based Gesture Recognition using Commodity WiFi

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Journal:2020 IEEE Wireless Communications and Networking Conference (WCNC)

Abstract:Device-free gesture recognition plays a crucial role in smart home applications, setting human free from wearable devices and causing no privacy concerns. Prior WiFi-based recognition systems have achieved high accuracy in a static environment, but with limitations in adapting changes in environments and locations. In this paper, we propose a fine-grained deep adaptation networks based gesture recognition scheme (DANGR) using the Channel State Information (CSI). DANGR applies wavelet transformation for amplitude denoising, and conjugate calibration to remove CSI time-variant random phase offse

Indexed by:Proceeding paper

Document Code:9120726

Document Type:C

ISSN No.:1525-3511

Translation or Not:no

Included Journals:EI