Abstract
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.
Highlights
With the continuous progress of science and technology, human-computer interaction technology has been developing rapidly
The flourish on the Internet of Things (IoT) and Artificial Intelligence (AI) has boosted human-machine interaction technology based on human gestures to become a hot topic in academia and industry
As the WLAN physical layer (PHY) information, channel state information (CSI) can be used in the fields of indoor localization [6], trajectory tracking [7, 8], gesture recognition [9,10,11], keystroke detection [12], driver activity [13], and lip-reading service [14], which is easy to implement and very sensitive to the changes of indoor environment, as well as in low cost
Summary
With the continuous progress of science and technology, human-computer interaction technology has been developing rapidly. Wireless Communications and Mobile Computing joint, and its recognition accuracy is high [17], while the user must carry the measuring equipment [18, 19], which will influence the experience of the user. It neither can make the user carry on the human-computer interaction more natural nor can it embody the human-computer interaction design. In order to recognize gestures accurately and make users get a better experience, a large number of researchers began to pay attention to the device-free gesture recognition technology without any measuring equipment.
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