WiGest: A ubiquitous WiFi-based gesture recognition system
WiGest: A ubiquitous WiFi-based gesture recognition system
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DOI：
10.5339/qfarc.2014.itpp1127
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发表时间：
2014-11
期刊：
影响因子：
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通讯作者：
Heba Abdelnasser;M. Youssef;Khaled A. Harras
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文献类型：
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作者：
Heba Abdelnasser;M. Youssef;Khaled A. Harras
我们介绍WiGest：一个利用WiFi信号强度变化来感知用户移动设备周围的空中手势的系统。与相关工作相比，WiGest的独特之处在于使用标准WiFi设备，不需要修改，也不需要进行手势识别培训。该系统识别出不同的信号变化原语，并以此构建相互独立的手势族。这些族可以映射到可区分的应用程序操作。我们解决了各种各样的挑战，包括清理噪声信号，手势类型和属性检测，减少由于人为干扰而产生的误报，以及适应不断变化的信号极性。我们使用现成的笔记本电脑实现了一个概念验证原型，并在办公环境和带有标准WiFi接入点的典型公寓中广泛评估了该系统。我们的结果表明，WiGest仅使用单个AP检测基本原语的准确率为87.5%，包括穿墙的非视线场景。使用三个偷听ap时，准确度提高到96%。此外，在使用多媒体播放器应用程序对系统进行评估时，我们的分类准确率达到了96%。这种准确性对于其他干扰人类的存在是稳健的，突出了WiGest的能力，使未来无处不在的基于手势的移动设备交互成为可能。
We present WiGest: a system that leverages changes in WiFi signal strength to sense in-air hand gestures around the user's mobile device. Compared to related work, WiGest is unique in using standard WiFi equipment, with no modifications, and no training for gesture recognition. The system identifies different signal change primitives, from which we construct mutually independent gesture families. These families can be mapped to distinguishable application actions. We address various challenges including cleaning the noisy signals, gesture type and attributes detection, reducing false positives due to interfering humans, and adapting to changing signal polarity. We implement a proof-of-concept prototype using off-the-shelf laptops and extensively evaluate the system in both an office environment and a typical apartment with standard WiFi access points. Our results show that WiGest detects the basic primitives with an accuracy of 87.5% using a single AP only, including through-the-wall non-line-of-sight scenarios. This accuracy increases to 96% using three overheard APs. In addition, when evaluating the system using a multi-media player application, we achieve a classification accuracy of 96%. This accuracy is robust to the presence of other interfering humans, highlighting WiGest's ability to enable future ubiquitous hands-free gesture-based interaction with mobile devices.