SMART: screen-based gesture recognition on commodity mobile devices

Zimo Liao, Zhicheng Luo, Qianyi Huang, Linfeng Zhang, Fan Wu, Qian Zhang, Yi Wang, Guihai Chen
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引用次数: 0

Abstract

In-air gesture control extends a touch screen and enables contactless interaction, thus has become a popular research direction in the past few years. Prior work has implemented this functionality based on cameras, acoustic signals, and Wi-Fi via existing hardware on commercial devices. However, these methods have low user acceptance. Solutions based on cameras and acoustic signals raise privacy concerns, while WiFi-based solutions are vulnerable to background noise. As a result, these methods are not commercialized and recent flagship smartphones have implemented in-air gesture recognition by adding extra hardware on-board, such as mmWave radar and depth camera. The question is, can we support in-air gesture control on legacy devices without any hardware modifications? In this demo, we design and implement SMART, an in-air gesture recognition system leveraging the screen and ambient light sensor (ALS), which are ordinary modalities on mobile devices. We implement SMART on a tablet. Results show that SMART can recognize 9 types of frequently used in-air gestures with an average accuracy of 96.1%.
SMART:商品移动设备上基于屏幕的手势识别
空中手势控制扩展了触摸屏,实现了非接触式交互,成为近年来研究的热门方向。之前的工作已经通过商用设备上的现有硬件,基于摄像头、声学信号和Wi-Fi实现了这一功能。然而,这些方法的用户接受度很低。基于摄像头和声学信号的解决方案会引起隐私问题,而基于wifi的解决方案容易受到背景噪音的影响。因此,这些方法没有商业化,最近的旗舰智能手机已经通过增加额外的硬件来实现空中手势识别,如毫米波雷达和深度摄像头。问题是,我们能否在不修改硬件的情况下支持传统设备的空中手势控制?在这个演示中,我们设计并实现了SMART,一个利用屏幕和环境光传感器(ALS)的空中手势识别系统,这是移动设备上的普通模式。我们在平板电脑上实现SMART。结果表明,SMART可以识别9种常用的空中手势,平均准确率为96.1%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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