Abstract
Interactive applications, such as somatic games, attract various researches on developing robust human-computer interfaces (HCI) to improve user experiences. Inspired by recent advances in RF-based human sensing, we seek to extract motion-induced Doppler effects using Channel State Information (CSI) provided on commercial WiFi devices. Our work is motivated from the observation that the direction of motion will lead to different frequency shift, which could be extracted and used to isolate the detailed directions from ambiguous trajectory. In this paper, we prototype WiSome, a contactless somatic game with off-the-shelf WiFi, which is able to accurately recognize the player’s movements with different directions without training. Extensive experiments validate that WiSome is superior to the previous methods, which could reach to an overall recognition accuracy of 95.4%.
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Acknowledgments
This work is supported by National Natural Science Foundation of China under Grant Nos. 61402394, 61379064, National Science Foundation of Jiangsu Province of China under Grant No. BK20140462, Natural Science Foundation of the Higher Education Institutions of Jiangsu Province of China under Grant No. 14KJB520040, China Postdoctoral Science Foundation funded project under Grant No. 2016M591922, Jiangsu Planned Projects for Postdoctoral Research Funds under Grant No. 1601162B, Industry university research project in Jiangsu Province under Grant No.72661632205A, Prospective joint research project of Jiangsu Province under Grant No. BY2016066-04, and sponsored by Qing Lan Project.
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Yang, H., Zhu, L., Lv, W. (2017). A HCI Motion Recognition System Based on Channel State Information with Fine Granularity. In: Ma, L., Khreishah, A., Zhang, Y., Yan, M. (eds) Wireless Algorithms, Systems, and Applications. WASA 2017. Lecture Notes in Computer Science(), vol 10251. Springer, Cham. https://doi.org/10.1007/978-3-319-60033-8_66
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DOI: https://doi.org/10.1007/978-3-319-60033-8_66
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