演示:使用毫米波传感器的免提人体活动识别

Soo Min Kwon, Song Yang, Jian Liu, X. Yang, Wesam Saleh, Shreya Patel, Christine Mathews, Yingying Chen
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引用次数: 12

摘要

在这个演示中,我们介绍了一个利用毫米波(mmWave)传感器的免提人体活动识别框架。与其他现有方法相比,我们的网络保护用户隐私,并可以重塑执行活动的人类骨架。此外,我们表明,我们的网络可以在一个架构中实现,并进一步优化,比那些只能得到单一结果(即只得到姿态估计或活动识别)的网络具有更高的精度。为了证明我们模型的实用性和鲁棒性,我们将在不同的设置(即面对不同的背景)中演示我们的模型,并有效地展示我们网络的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Demo: Hands-Free Human Activity Recognition Using Millimeter-Wave Sensors
In this demo, we introduce a hands-free human activity recognition framework leveraging millimeter-wave (mmWave) sensors. Compared to other existing approaches, our network protects user privacy and can remodel a human skeleton performing the activity. Moreover, we show that our network can be achieved in one architecture, and be further optimized to have higher accuracy than those that can only get singular results (i.e. only get pose estimation or activity recognition). To demonstrate the practicality and robustness of our model, we will demonstrate our model in different settings (i.e. facing different backgrounds) and effectively show the accuracy of our network.
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