Device-Free and Training-Free Hand Gesture Recognition with Acoustic Signal.
2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)(2023)
摘要
Hand gesture recognition is an essential Human Computer Interaction (HCI) mechanism for users to control smart devices. While traditional device-based methods support acceptable recognition performance, the recent advance in wireless sensing could enable device-free hand gesture recognition. However, two severe limitations are serious environmental interference and high-cost hardware, which hamper the wide deployment. This paper proposes a novel system TaGesture, which employ the inaudible acoustic signal to realize device-free and training-free hand gesture recognition with a pair of commercial speaker and microphone array. We address unique technical challenges, such as proposing a novel acoustic hand tracking smoothing algorithm with Interaction Multiple Model (IMM) Kalman Filter to address the issue of localization angle ambiguity, and designing a classification algorithm to realize acoustic-based hand gesture recognition without training. Comprehensive experiments are conducted to evaluate TaGesture. Results show that it can achieve a total accuracy of 97.5% for acoustic-based hand gesture recognition, and support the furthest sensing range of up to 3 m.
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关键词
Hand gesture recognition,Inaudible acoustic sensing,Training-free sensing,Device-free sensing
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