基于多普勒效应的多波复杂手势识别

Corey R. Pittman, J. Laviola
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引用次数: 14

摘要

我们建立了一个声学的,基于手势的识别系统,叫做Multiwave,它利用多普勒效应将多维运动转化为用户界面命令。我们的系统只需要使用扬声器和麦克风就可以操作,但可以增加更多的扬声器。由于这些组件已经包含在大多数终端用户系统中,我们的设计使基于手势的输入更容易被更广泛的终端用户访问。我们能够通过从多个扬声器中产生已知的高频音调来检测复杂的手势,并通过声波的变化来检测运动。我们展示了对Multiwave的用户研究结果,以评估不同手势的识别率,并报告与当前技术相当或更好的错误率,尽管有额外的复杂性。我们还报告了主观用户反馈和从我们的系统中吸取的一些经验教训,为多维声学手势识别的未来应用提供了额外的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiwave: Complex Hand Gesture Recognition Using the Doppler Effect
We built an acoustic, gesture-based recognition system called Multiwave, which leverages the Doppler Effect to translate multidimensional movements into user interface commands. Our system only requires the use of a speaker and microphone to be operational, but can be augmented with more speakers. Since these components are already included in most end user systems, our design makes gesture-based input more accessible to a wider range of end users. We are able to detect complex gestures by generating a known high frequency tone from multiple speakers and detecting movement using changes in the sound waves. We present the results of a user study of Multiwave to evaluate recognition rates for different gestures and report error rates comparable to or better than the current state of the art despite additional complexity. We also report subjective user feedback and some lessons learned from our system that provide additional insight for future applications of multidimensional acoustic gesture recognition.
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CiteScore
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