TR2020-158
Human Pose and Seat Occupancy Classification with Commercial MMWave WiFi
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- "Human Pose and Seat Occupancy Classification with Commercial MMWave WiFi", IEEE Global Communications Conference (GLOBECOM), DOI: 10.1109/GCWkshps50303.2020.9367535, December 2020.BibTeX TR2020-158 PDF
- @inproceedings{Yu2020dec,
- author = {Yu, Jianyuan and Wang, Pu and Koike-Akino, Toshiaki and Wang, Ye and Orlik, Philip V.},
- title = {Human Pose and Seat Occupancy Classification with Commercial MMWave WiFi},
- booktitle = {IEEE Global Communications Conference (GLOBECOM)},
- year = 2020,
- month = dec,
- publisher = {IEEE},
- doi = {10.1109/GCWkshps50303.2020.9367535},
- isbn = {978-1-7281-7307-8},
- url = {https://www.merl.com/publications/TR2020-158}
- }
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- "Human Pose and Seat Occupancy Classification with Commercial MMWave WiFi", IEEE Global Communications Conference (GLOBECOM), DOI: 10.1109/GCWkshps50303.2020.9367535, December 2020.
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MERL Contacts:
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Research Areas:
Communications, Computational Sensing, Machine Learning, Signal Processing
Abstract:
Our previous studies introduced a mid-grained intermediate-level channel measurement — spatial beam signalto-noise ratios (SNRs) that are inherently available and defined in the 60-GHz IEEE 802.11ad/ay standards — for the fingerprinting-based indoor localization. In this paper, we take one step further to use the mid-grained channel measurement for human monitoring applications including human pose and seat occupancy classifications. The effectiveness of the mid-grained channel measurement is validated by an in-house experimental dataset that includes 5 separate data collection sessions using classical classification methods and modern deep neural networks. Our preliminary result shows that mmWave beam SNRs are capable of delivering high classification accuracy above 90%.
Related News & Events
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NEWS MERL published four papers in 2020 IEEE Global Communications Conference Date: December 7, 2020 - December 11, 2020
Where: Taipei, Taiwan
MERL Contacts: Kyeong Jin (K.J.) Kim; Toshiaki Koike-Akino; Philip Orlik; Pu (Perry) Wang; Ye Wang
Research Areas: Communications, Computational Sensing, Machine Learning, Signal ProcessingBrief- MERL researchers have published four papers in 2020 IEEE Global Communications Conference (GlobeComm). This conference is one of the two IEEE Communications Societies flagship conferences dedicated to Communications for Human and Machine Intelligence. Topics of the published papers include, transmit diversity schemes, coding for molecular networks, and location and human activity sensing via WiFi signals.