Air Gesture Recognition Using WLAN Physical Layer Information
Joint Authors
Hao, Zhanjun
Dang, Xiaochao
Liu, Yang
Tang, Xuhao
Shao, Chenguang
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-13
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Information Technology and Computer Science
Abstract EN
In recent years, the researchers have witnessed the important role of air gesture recognition in human-computer interactive (HCI), smart home, and virtual reality (VR).
The traditional air gesture recognition method mainly depends on external equipment (such as special sensors and cameras) whose costs are high and also with a limited application scene.
In this paper, we attempt to utilize channel state information (CSI) derived from a WLAN physical layer, a Wi-Fibased air gesture recognition system, namely, WiNum, which solves the problems of users’ privacy and energy consumption compared with the approaches using wearable sensors and depth cameras.
In the process of recognizing the WiNum method, the collected raw data of CSI should be screened, among which can reflect the gesture motion.
Meanwhile, the screened data should be preprocessed by noise reduction and linear transformation.
After preprocessing, the joint of amplitude information and phase information is extracted, to match and recognize different air gestures by using the S-DTW algorithm which combines dynamic time warping algorithm (DTW) and support vector machine (SVM) properties.
Comprehensive experiments demonstrate that under two different indoor scenes, WiNum can achieve higher recognition accuracy for air number gestures; the average recognition accuracy of each motion reached more than 93%, in order to achieve effective recognition of air gestures.
American Psychological Association (APA)
Dang, Xiaochao& Liu, Yang& Hao, Zhanjun& Tang, Xuhao& Shao, Chenguang. 2020. Air Gesture Recognition Using WLAN Physical Layer Information. Wireless Communications and Mobile Computing،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1214537
Modern Language Association (MLA)
Dang, Xiaochao…[et al.]. Air Gesture Recognition Using WLAN Physical Layer Information. Wireless Communications and Mobile Computing No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1214537
American Medical Association (AMA)
Dang, Xiaochao& Liu, Yang& Hao, Zhanjun& Tang, Xuhao& Shao, Chenguang. Air Gesture Recognition Using WLAN Physical Layer Information. Wireless Communications and Mobile Computing. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1214537
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214537