Wi-SL: Contactless Fine-Grained Gesture Recognition Uses Channel State Information.

Sensors
Zhanjun HaoDaiyang Zhang

Abstract

In recent years, with the development of wireless sensing technology and the widespread popularity of WiFi devices, human perception based on WiFi has become possible, and gesture recognition has become an active topic in the field of human-computer interaction. As a kind of gesture, sign language is widely used in life. The establishment of an effective sign language recognition system can help people with aphasia and hearing impairment to better interact with the computer and facilitate their daily life. For this reason, this paper proposes a contactless fine-grained gesture recognition method using Channel State Information (CSI), namely Wi-SL. This method uses a commercial WiFi device to establish the correlation mapping between the amplitude and phase difference information of the subcarrier level in the wireless signal and the sign language action, without requiring the user to wear any device. We combine an efficient denoising method to filter environmental interference with an effective selection of optimal subcarriers to reduce the computational cost of the system. We also use K-means combined with a Bagging algorithm to optimize the Support Vector Machine (SVM) classification (KSB) model to enhance the classification ...Continue Reading

References

Apr 5, 2011·Computer Methods and Programs in Biomedicine·Saeid Amiri, Dietrich von Rosen
Dec 20, 2014·Sensors·Mohammadreza Balouchestani, Sridhar Krishnan
Aug 28, 2019·Sensors·Zhanjun HaoChenguang Shao

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Methods Mentioned

BETA
feature extraction
chip
PCA

Software Mentioned

WiSee
Xshell
Atheros CSI - Tool
CyberGlove
SL
Gest
Openwrt
Windows
WiMorse
WinSCP2

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