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| Content Provider | ACM Digital Library |
|---|---|
| Author | Qian, Kun Liu, Yunhao Wu, Chenshu Zhou, Zimu Zheng, Yue Yang, Zheng |
| Abstract | In-air interaction acts as a key enabler for ambient intelligence and augmented reality. As an increasing popular example, exergames, and the alike gesture recognition applications, have attracted extensive research in designing accurate, pervasive and low-cost user interfaces. Recent advances in wireless sensing show promise for a ubiquitous gesture-based interaction interface with Wi-Fi. In this work, we extract complete information of motion-induced Doppler shifts with only commodity Wi-Fi. The key insight is to harness antenna diversity to carefully eliminate random phase shifts while retaining relevant Doppler shifts. We further correlate Doppler shifts with motion directions, and propose a light-weight pipeline to detect, segment, and recognize motions without training. On this basis, we present WiDance, a Wi-Fi-based user interface, which we utilize to design and prototype a contactless dance-pad exergame. Experimental results in typical indoor environment demonstrate a superior performance with an accuracy of 92%, remarkably outperforming prior approaches. |
| Starting Page | 1961 |
| Ending Page | 1972 |
| Page Count | 12 |
| File Format | |
| ISBN | 9781450346559 |
| DOI | 10.1145/3025453.3025678 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2017-05-02 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Off-the-shelf wi-fi Wireless sensing Motion direction recognition Exergame |
| Content Type | Text |
| Resource Type | Article |
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