Title :
WiG: WiFi-Based Gesture Recognition System
Author :
Wenfeng He;Kaishun Wu;Yongpan Zou;Zhong Ming
Author_Institution :
Guangdong Province Key Lab. of Popular High Performance Comput., Shenzhen Univ., Shenzhen, China
Abstract :
Most recently, gesture recognition has increasingly attracted intense academic and industrial interest due to its various applications in daily life, such as home automation, mobile games. Present approaches for gesture recognition, mainly including vision-based, sensor-based and RF-based, all have certain limitations which hinder their practical use in some scenarios. For example, the vision-based approaches fail to work well in poor light conditions and the sensor-based ones require users to wear devices. To address these, we propose WiG in this paper, a device-free gesture recognition system based solely on Commercial Off-The-Shelf (COTS) WiFi infrastructures and devices. Compared with existing Radio Frequency (RF)-based systems, WiG stands out for its systematic simplicity, extremely low cost and high practicability. We implemented WiG in indoor environment and conducted experiments to evaluate its performance in two typical scenarios. The results demonstrate that WiG can achieve an average recognition accuracy of 92% in line-of-sight scenario and average accuracy of 88% in the none-line-of sight scenario.
Keywords :
"Gesture recognition","Feature extraction","Wireless communication","Wireless sensor networks","Support vector machines","OFDM","IEEE 802.11 Standard"
Conference_Titel :
Computer Communication and Networks (ICCCN), 2015 24th International Conference on
DOI :
10.1109/ICCCN.2015.7288485