Mission: mmWave Radar Person Identification with RGB Cameras
This paper presents Mission, the first-of-this-kind cross-modal reidentification (ReID) design for mmWave Radar and RGB cameras. Given a person of interest detected by Radar in camera-restricted scenarios, Mission can identify the image of the person from cameras that are ubiquitously deployed in camera-allowed areas. We envision that cross Vison-RF ReID can significantly enrich mmWave human sensing with a wide spectrum of applications in security surveillance, tracking, and personalized services. Technically, we introduce a novel method for cross-modal similarity estimation that exploits inherent synergies between fine-grained 2D images and coarse-grained 3D Radar point clouds to effectively overcome their modal discrepancy. Through extensive experiments, we demonstrated that our proposed system can achieve 85% top-1 accuracy and 90% top-5 accuracy among 58 volunteers.
Authors
- Tianshun Yao (ORCID: https://orcid.org/0000-0001-7530-1420)
- Ruofeng Liu (ORCID: https://orcid.org/0000-0001-9804-3727)
- Zhimeng Yin (ORCID: https://orcid.org/0000-0002-3548-3335)
- Wenchao Jiang (ORCID: https://orcid.org/0000-0001-6765-2466)
- Ruixia Shi (ORCID: https://orcid.org/0009-0008-0637-195X)
- Shuai Wang (ORCID: https://orcid.org/0000-0003-2766-1135)
- Luoyu Mei (ORCID: https://orcid.org/0000-0003-2338-0256)
- Shuai Wang (ORCID: https://orcid.org/0000-0002-3609-2205)
Institutions
- Singapore University of Technology and Design (SG)
- City University of Hong Kong (HK)
- Michigan United (US)
- Southeast University (CN)
- Michigan State University (US)
Publication Details
- Published
- 2024-11-04
- DOI
- https://doi.org/10.1145/3666025.3699340
- Citations
- 10
- Primary Topic
- Biometric Identification and Security
- Type
- article
- Field-Weighted Citation Impact
- 3.50