The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
mID: Tracking and Identifying People with Millimeter Wave Radar
Abstract
The key to offering personalised services in smart spaces is knowing where a particular person is with a high degree of accuracy. Visual tracking is one such solution, but concerns arise around the potential leakage of raw video information and many people are not comfortable accepting cameras in their homes or workplaces. We propose a human tracking and identification system (mID) based on millimeter wave radar which has a high tracking accuracy, without being visually compromising. Unlike competing techniques based on WiFi Channel State Information (CSI), it is capable of tracking and identifying multiple people simultaneously. Using a lowcost, commercial, off-the-shelf radar, we first obtain sparse point clouds and form temporally associated trajectories. With the aid of a deep recurrent network, we identify individual users. We evaluate and demonstrate our system across a variety of scenarios, showing median position errors of 0.16 m and identification accuracy of 89% for 12 people.
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Cites
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
Cited by
RadHAR: Human Activity Recognition from Point Clouds Generated through a Millimeter-wave Radar
Singh, A. D., Sandha, S. S., Garcia, L., & Srivastava, M. (2019) · Proceedings of the 3rd ACM Workshop on Millimeter-wave Networks and Sensing Systems · doi:10.1145/3349624.3356768 · Cited by 303
Metadata
- Authors
- Zhao, P., Lu, C. X., Wang, J., Chen, C., Wang, W., Trigoni, N., & Markham, A.
- Venue
- 2019 15th International Conference on Distributed Computing in Sensor Systems (DCOSS)
- Publisher
- IEEE
- Published
- 2019-05
- Pages
- 33-40
- OpenAlex
- W2949860773
- Cited by
- 266
- References
- 1
- FWCI
- 42.61
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Zhao, P., Lu, C. X., Wang, J., Chen, C., Wang, W., Trigoni, N., & Markham, A. (2019). mID: Tracking and Identifying People with Millimeter Wave Radar. 2019 15th International Conference on Distributed Computing in Sensor Systems (DCOSS). https://doi.org/10.1109/dcoss.2019.00028
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