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 paper, 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%, respectively.

中文翻译：

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基于 WiFi 的多用户手势识别

在过去几年中，基于 WiFi 的手势识别受到了极大的关注。然而，现有基于 WiFi 的手势识别系统的关键限制是它们无法识别多个用户同时执行它们的手势。在本文中，我们解决了这个限制并提出了 WiMU，一种基于 WiFi 的多用户手势识别系统。WiMU 背后的关键思想是，当它检测到一些用户同时执行了一些手势时，它首先自动确定同时执行的手势数量（$N_a$），然后使用从单个用户收集的训练样本，生成虚拟样本对于 $N_a$ 手势的各种合理组合。这些虚拟样本的关键特性是任何给定手势组合的虚拟样本与真实用户执行该手势组合所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。我们使用商用 WiFi 设备实施并广泛评估了 WiMU。我们的结果表明，WiMU 可以识别 2、3、4、5、6、7 和 8 个同时执行的手势，准确率分别为 95.6、94.9、93.9、92.7、91.6、91.0 和 90.1%。