CTrack: Acoustic Device-Free and Collaborative Hands Motion Tracking on Smartphones
CTrack: Acoustic Device-Free and Collaborative Hands Motion Tracking on Smartphones
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CTrack：智能手机上的无声学设备和协作式手部运动跟踪
DOI：
10.1109/jiot.2021.3071287
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发表时间：
2021-10-01
影响因子：
10.6
通讯作者：
Zhou, Siwang
中科院分区：
文献类型：
--
作者：
Jiang, Hongbo;Wang, Minglin;Zhou, Siwang
在移动终端上启用非接触式和无设备的手部跟踪带来了新的用户交互体验。在这篇文章中，我们提出了CTrack，一个无设备和协作的手运动跟踪解决方案，通过使用声学信号的设备上的交互。CTrack不需要用传感器测量手。我们通过将设备转换为主动声纳系统来实现这一目标，该系统可以传输听不见的声音信号并跟踪麦克风处的手部回声。为了保证亚厘米级的跟踪精度，我们提出了一种自适应的方法，使用啁啾的飞行时间来准确地测量从手到内置扬声器阵列的距离。然后，手、扬声器阵列和麦克风阵列产生一组不同的椭圆。通过求解和优化这些椭圆的交点，可以精确地定位手的位置。我们的评估表明，CTrack可以使用Nexus 6P的内置麦克风和扬声器实现平均精度为14 mm的2D运动跟踪。
Enabling contactless and device-free hands tracking on mobile device leads to new user interaction experiences. In this article, we propose CTrack, a device-free and collaborative hands motion tracking solution for above-device interaction by using acoustic signals. CTrack does not require instrumenting hands with sensors. We achieve this by transforming the device into an active sonar system that transmits inaudible sound signals and tracks the echoes of the hand at its microphones. To guarantee subcentimeter-level tracking accuracies, we present an adaptive approach that uses the chirp's time of flight to accurately measure the distance from the hand to an in-built speaker array. Then, the hand, speaker array, and microphone array yield a set of different ellipses. The hand position can be pinpointed exactly by solving and optimizing the intersection of these ellipses. Our evaluation shows that CTrack can achieve 2-D motion tracking with an average accuracy of 14 mm using the in-built microphones and speakers of a Nexus 6P.