Turning a Mobile Device into a Mouse in the Air
Turning a Mobile Device into a Mouse in the Air
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DOI：
10.1145/2742647.2742662
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发表时间：
2015-05
期刊：
影响因子：
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通讯作者：
Sangki Yun;Yi-Chao Chen;L. Qiu
中科院分区：
文献类型：
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作者：
Sangki Yun;Yi-Chao Chen;L. Qiu
鼠标由于其直观的使用而成为最成功的用户界面之一。随着越来越多的设备配备了显示器，并为用户提供了丰富的选择，传统的鼠标需要一个表面来操作已经不够了。虽然市场上有不同类型的空气鼠标，但它们依赖于加速度计和陀螺仪，这大大限制了准确性和易用性。在本文中，我们开发了一个系统，可以准确地跟踪手的运动来实现鼠标。我们的方案的一个独特优点是它使用移动的设备中已经可用的现有硬件（例如，智能电话和智能手表）和要控制的设备（例如，智能电视）。更具体地说，我们的方法以几个选定的频率发送听不见的声音脉冲，并使用频率偏移来估计速度和行进距离。然后，我们开发技术来快速校准扬声器之间的距离，并使用其移动轨迹缩小设备的初始位置。基于这些信息，我们连续地跟踪设备的真实的新位置。这是可行的，因为许多设备，如智能电视，PC和笔记本电脑，已经有多个扬声器。当只有一个扬声器可用时，我们可以利用声音的频移沿着接收到的WiFi信号的相位来实现跟踪。我们的评估和用户研究表明，我们的系统实现了高跟踪精度（例如，中位误差约为1.4cm）和易于使用。
A mouse has been one of the most successful user interfaces due to its intuitive use. As more devices are equipped with displays and offer rich options for users to choose from, a traditional mouse that requires a surface to operate is no longer sufficient. While different types of air mice are available in the market, they rely on accelerometers and gyroscopes, which significantly limit the accuracy and ease of use. In this paper, we develop a system that can accurately track hand movement to realize a mouse. A unique advantage of our scheme is that it achieves high tracking accuracy using the existing hardware already available in the mobile devices (e.g., smart phones and smart watches) and equipment to be controlled (e.g., smart TVs). More specifically, our approach sends inaudible sound pulses at a few selected frequencies, and uses the frequency shifts to estimate the speed and distance traveled. We then develop techniques to quickly calibrate the distance between speakers and narrow down the device's initial position using its movement trajectory. Based on the information, we continuously track the device's new position in real time. This is feasible because many devices, such as smart TVs, PCs, and laptops, already have multiple speakers. When only one speaker is available, we can leverage the frequency shift of sound along with the phase of received WiFi signal to enable tracking. Our evaluation and user study demonstrate that our system achieves high tracking accuracy (e.g., median error of around 1.4 cm) and ease of use.