TY - GEN
T1 - PWiG
T2 - 2018 International Conference on Computing, Networking and Communications, ICNC 2018
AU - Man, Dapeng
AU - Yang, Wu
AU - Wang, Xin
AU - Lv, Jiguang
AU - Du, Xiaojiang
AU - Yu, Miao
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/6/19
Y1 - 2018/6/19
N2 - With the development of the artificial intelligence, people hope that the advancement of the science and technology will continuously bring more convenience to their daily life. Therefore, gesture recognition has drawn more attentions. In the previous research, people paid their attentions on the aspect of the wearable devices and computer graphic. Although the recognition accuracy of previous methods is satisfactory under line-of-sight, the costs are very high and they require the users to be equipped with wearable sensors, which hinder their wide deployment. The development of wireless network provides convenience for solving this problem. Different gestures can be identified only according to the fluctuation of RSSI of wireless signals. But the intrinsic limitations of RSSI make it difficult to be feasible. Fortunately, CSI-based gesture recognition systems overcome the shortcomings above. In this paper, we propose a Phase-based Wireless Gesture recognition system PWiG, an accurate device-free gesture recognition approach. Compared with other existing gesture recognition systems, PWiG only needs commercial Wi-Fi devices to identify different gestures. PWiG uses the more sensitive phase information. Moreover, it reduces the hardware cost and greatly simplifies the process of the gesture extraction only by calculating the variance values. In addition, PWiG meets the standard of gesture recognition. According to the experimental results, PWiG achieves an average recognition accuracy of 94% in line-of-sight scenario and 89% in none-line-of-sight scenario.
AB - With the development of the artificial intelligence, people hope that the advancement of the science and technology will continuously bring more convenience to their daily life. Therefore, gesture recognition has drawn more attentions. In the previous research, people paid their attentions on the aspect of the wearable devices and computer graphic. Although the recognition accuracy of previous methods is satisfactory under line-of-sight, the costs are very high and they require the users to be equipped with wearable sensors, which hinder their wide deployment. The development of wireless network provides convenience for solving this problem. Different gestures can be identified only according to the fluctuation of RSSI of wireless signals. But the intrinsic limitations of RSSI make it difficult to be feasible. Fortunately, CSI-based gesture recognition systems overcome the shortcomings above. In this paper, we propose a Phase-based Wireless Gesture recognition system PWiG, an accurate device-free gesture recognition approach. Compared with other existing gesture recognition systems, PWiG only needs commercial Wi-Fi devices to identify different gestures. PWiG uses the more sensitive phase information. Moreover, it reduces the hardware cost and greatly simplifies the process of the gesture extraction only by calculating the variance values. In addition, PWiG meets the standard of gesture recognition. According to the experimental results, PWiG achieves an average recognition accuracy of 94% in line-of-sight scenario and 89% in none-line-of-sight scenario.
KW - Wi-Fi
KW - channel state information
KW - device-free
KW - gesture recognition
UR - http://www.scopus.com/inward/record.url?scp=85050148392&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85050148392&partnerID=8YFLogxK
U2 - 10.1109/ICCNC.2018.8390335
DO - 10.1109/ICCNC.2018.8390335
M3 - Conference contribution
AN - SCOPUS:85050148392
T3 - 2018 International Conference on Computing, Networking and Communications, ICNC 2018
SP - 837
EP - 842
BT - 2018 International Conference on Computing, Networking and Communications, ICNC 2018
Y2 - 5 March 2018 through 8 March 2018
ER -