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Whole-home gesture recognition using wireless signals
Abstract
This paper presents WiSee, a novel gesture recognition system that leverages wireless signals (e.g., Wi-Fi) to enable whole-home sensing and recognition of human gestures. Since wireless signals do not require line-of-sight and can traverse through walls, WiSee can enable whole-home gesture recognition using few wireless sources. Further, it achieves this goal without requiring instrumentation of the human body with sensing devices. We implement a proof-of-concept prototype of WiSee using USRP-N210s and evaluate it in both an office environment and a two- bedroom apartment. Our results show that WiSee can identify and classify a set of nine gestures with an average accuracy of 94%.
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Cited by
Understanding and Modeling of WiFi Signal Based Human Activity Recognition
Wang, W., Liu, A. X., Shahzad, M., Ling, K., & Lu, S. (2015) · Proceedings of the 21st Annual International Conference on Mobile Computing and Networking · doi:10.1145/2789168.2790093 · Cited by 1,110
Soli: ubiquitous gesture sensing with millimeter wave radar
Lien, J., Gillian, N., Karagozler, M. E., Amihood, P., Schwesig, C., Olson, E., Raja, H., & Poupyrev, I. (2016) · ACM Transactions on Graphics · doi:10.1145/2897824.2925953 · Cited by 957
WiFall: Device-Free Fall Detection by Wireless Networks
Wang, Y., Wu, K., & Ni, L. M. (2017) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2016.2557792 · Cited by 836
Zero-Effort Cross-Domain Gesture Recognition with Wi-Fi
Zheng, Y., Zhang, Y., Qian, K., Zhang, G., Liu, Y., Wu, C., & Yang, Z. (2019) · Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services · doi:10.1145/3307334.3326081 · Cited by 557
Emotion recognition using wireless signals
Zhao, M., Adib, F., & Katabi, D. (2016) · Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking · doi:10.1145/2973750.2973762 · Cited by 461
Metadata
- Authors
- Pu, Q., Gupta, S., Gollakota, S., & Patel, S.
- Venue
- Proceedings of the 19th annual international conference on Mobile computing & networking - MobiCom '13
- Publisher
- ACM Press
- Published
- 2013
- Pages
- 27
- OpenAlex
- W2141336889
- Cited by
- 1,109
- References
- 0
- Type
- conference abstract
- Language
- en
- Open access
- closed
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- Pu, Q., Gupta, S., Gollakota, S., & Patel, S. (2013). Whole-home gesture recognition using wireless signals. Proceedings of the 19th annual international conference on Mobile computing & networking - MobiCom '13. https://doi.org/10.1145/2500423.2500436
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