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WiFi based Multi-User Gesture Recognition

机译:基于WiFi的多用户手势识别

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WiFi based gesture recognition has received significant attention over the past few years. However, the key limitation of prior WiFi based gesture recognition systems is that they cannot recognize the gestures of multiple users performing them simultaneously. In this article, we address this limitation and propose WiMU, a WiFi based Multi-User gesture recognition system. The key idea behind WiMU is that when it detects that some users have performed some gestures simultaneously, it first automatically determines the number of simultaneously performed gestures (N-a) and then, using the training samples collected from a single user, generates virtual samples for various plausible combinations of N-a gestures. The key property of these virtual samples is that the virtual samples for any given combination of gestures are identical to the real samples that would result from real users performing that combination of gestures. WiMU compares the detected sample against these virtual samples and recognizes the simultaneously performed gestures. We implemented and extensively evaluated WiMU using commodity WiFi devices. Our results show that WiMU recognizes 2, 3, 4, 5, 6, 7, and 8 simultaneously performed gestures with accuracies of 95.6, 94.9, 93.9, 92.7, 91.6, 91.0, and 90.1 percent, respectively.
机译:基于WiFi的手势识别在过去几年中受到了重大关注。然而,基于WiFi的手势识别系统的主要限制是它们不能识别同时执行它们的多个用户的手势。在本文中,我们解决了基于WiFi的多用户手势识别系统的这个限制并提出了Wimu。 WiMu背后的关键想法是,当它检测到某些用户同时执行一些手势时,它首先自动确定同时执行的手势(NA),然后使用从单个用户收集的训练样本来生成各种虚拟样本Na手势的可粘性组合。这些虚拟样本的关键属性是,用于任何给定手势组合的虚拟样本与由执行手势组合的真实用户产生的真实样本相同。 WiMU将检测到的样本与这些虚拟样本进行比较,并识别同时执行的手势。我们使用商品WiFi设备实施和广泛地评估了WiMU。我们的研究结果表明,Wimu分别识别2,3,4,5,6,7和8,同时进行的姿势,精度分别为95.6,94.9,93.9,92.7,91.6,91.0和90.1%。

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