Accurate Acoustic Based Gesture Classification with Zero Start-Up Cost

Ai, Haojun; Han, L.; Wang, Yifeng; Liao, Liang

doi:10.1007/978-3-030-05057-3_4

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…In recent years, quite a number of studies of hand gesture recognition have increasingly emerged. Based on their purposes, these applications usually employ different hardware equipment to emit and receive sound signal, including smartwatch [81]- [83], computer [84]- [90], specially designed device [91]- [96], and transceiver in environment [97], [98].…”

Section: Introductionmentioning

confidence: 99%

Hand Gesture Recognition Based on Active Ultrasonic Sensing of Smartphone: A Survey

et al. 2019

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With the rapid development of Internet of Things, hand gesture recognition has drawn wide attention in the field of ubiquitous computing because it provides us with simple and natural human-computer interaction mode. Among these various implementations, hand gesture recognition using ultrasonic signals of smartphone has become a hot research topic due to its various advantages. In this paper, we consider the smartphone as an active sonar sensing system to identify hand movements. Specifically, the speakers emit ultrasonic signal and the microphone on the same phone receives the changed echo affected by hand movements. This paper investigates the state-of-the-art hand gesture applications and presents a comprehensive survey on the characteristics of studies using the active sonar sensing system. Firstly, we review the existing research of hand gesture recognition based on acoustic signals. After that, we introduce the characteristics of ultrasonic signal and describe the fundamental principle of hand gesture recognition. Then, we focus on the typical methods used in these studies and present a detailed analysis on signal generation, feature extraction, preprocessing, and recognition methods. Next, we investigate the state-of-the-art ultrasonic-based applications of hand gesture recognition using smartphone and analyze them in detail from dynamic gesture recognition and hand tracking. Afterwards, we make a discussion about these systems from signal acquisition, signal processing, and performance evaluation to obtain some insight into development of the ultrasonic hand gesture recognition system. Finally, we conclude by discussing the challenges, insight, and open issues involved in hand gesture recognition based on ultrasonic signal of the smartphone.

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