The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Gait recognition using wifi signals
Open accessAbstract
In this paper, we propose WifiU, which uses commercial WiFi devices to capture fine-grained gait patterns to recognize humans. The intuition is that due to the differences in gaits of different people, the WiFi signal reflected by a walking human generates unique variations in the Channel State Information (CSI) on the WiFi receiver. To profile human movement using CSI, we use signal processing techniques to generate spectrograms from CSI measurements so that the resulting spectrograms are similar to those generated by specifically designed Doppler radars. To extract features from spectrograms that best characterize the walking pattern, we perform autocorrelation on the torso reflection to remove imperfection in spectrograms. We evaluated WifiU on a dataset with 2,800 gait instances collected from 50 human subjects walking in a room with an area of 50 square meters. Experimental results show that WifiU achieves top-1, top-2, and top-3 recognition accuracies of 79.28%, 89.52%, and 93.05%, respectively.
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Cites
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Understanding and Modeling of WiFi Signal Based Human Activity Recognition
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Self-citationWhole-home gesture recognition using wireless signals
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Gait Analysis: An Introduction
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Human Activity Classification Based on Micro-Doppler Signatures Using a Support Vector Machine
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Cited by
WiFi Sensing with Channel State Information: A Survey
Ma, Y., Zhou, G., & Wang, S. (2020) · ACM Computing Surveys · doi:10.1145/3310194 · Cited by 869
Through-Wall Human Pose Estimation Using Radio Signals
Zhao, M., Li, T., Alsheikh, M. A., Tian, Y., Zhao, H., Torralba, A., & Katabi, D. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00768 · Cited by 658
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
FarSense: Pushing the Range Limit of WiFi-based Respiration Sensing with CSI Ratio of Two Antennas
Zeng, Y., Wu, D., Xiong, J., Yi, E., Gao, R., & Zhang, D. (2019) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies · doi:10.1145/3351279 · Cited by 469
Wireless Sensing for Human Activity: A Survey
Liu, J., Liu, H., Chen, Y., Wang, Y., & Wang, C. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2934489 · Cited by 414
Metadata
- Authors
- Wang, W., Liu, A. X., & Shahzad, M.
- Venue
- Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing
- Publisher
- ACM
- Published
- 2016-09-12
- Pages
- 363-373
- OpenAlex
- W2517331439
- Cited by
- 567
- References
- 32
- FWCI
- 109.73
- Type
- conference paper
- Language
- en
- Open access
- bronze
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