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https://hdl.handle.net/10356/166279
Title: | Interpersonal distance tracking with mmWave radar and IMUs | Authors: | Dai, Yimin | Keywords: | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence | Issue Date: | 2023 | Publisher: | Nanyang Technological University | Source: | Dai, Y. (2023). Interpersonal distance tracking with mmWave radar and IMUs. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166279 | Abstract: | Tracking interpersonal distances is essential for real-time social distancing management and ex-post contact tracing to prevent spreads of contagious diseases. Bluetooth neighbor discovery has been employed for such purposes in combating COVID-19, but does not provide satisfactory spatiotemporal resolutions. This paper presents ImmTrack, a system that uses a millimeter wave radar and exploits the inertial measurement data from user-carried smartphones or wearables to track interpersonal distances. By matching the movement traces reconstructed from the radar and inertial data, the pseudo identities of the inertial data can be transferred to the radar sensing results in the global coordinate system. The re-identified, radar-sensed movement trajectories are then used to track interpersonal distances. In a broader sense, ImmTrack is the first system that fuses data from millimeter wave radar and inertial measurement units for simultaneous user tracking and re-identification. Evaluation with up to 27 people in various indoor/outdoor environments shows ImmTrack's decimeters-seconds spatiotemporal accuracy in contact tracing, which is similar to that of the privacy-intrusive camera surveillance and significantly outperforms the Bluetooth neighbor discovery approach. | URI: | https://hdl.handle.net/10356/166279 | DOI: | 10.32657/10356/166279 | Schools: | School of Computer Science and Engineering | Rights: | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Theses |
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Yimin-MENG-thesis-updated-v2.pdf | 6.76 MB | Adobe PDF | ![]() View/Open |
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