A Survey of Pedestrian Re-Identification Based on Millimeter Wave Radar and Vision Fusion
With the advancement of technology and the growth of human demand, pedestrian re-identification is a key technology of intelligent systems and plays an important role in daily life. Traditional vision methods have certain limitations, but the millimeter-wave-vision fusion system, which complements the advantages of cameras and millimeter-wave radars, plays a greater role and is attracting widespread attention. This paper first introduces the effects of vision camera and millimeter-wave radar camera on human re-identification in a single mode, and then discusses the detailed processing required to fuse the data of the two modes, including the key technologies of sensor settings, data synchronization and sensor calibration. We also review the classification and evolution of millimeter-wave radar and visual fusion pedestrian re-identification methods, including data-level, feature-level and decision-level methods, and review the previous research methods, which will provide great inspiration for future research. Finally, this paper discusses the typical applications of millimeter-wave vision fusion systems, as well as the key technologies and potential challenges of fusing millimeter-wave radar and visual data, and looks forward to future research directions.
Authors
- Tao Jiang (ORCID: https://orcid.org/0000-0001-5281-5330)
- Zhihao Deng (ORCID: https://orcid.org/0000-0002-8741-1560)
- Qingyuan Yang (ORCID: https://orcid.org/0000-0003-4481-157X)
- Zhengjie Wang (ORCID: https://orcid.org/0000-0003-3179-3026)
- Xinran Qiu
- Jingxuan Li (ORCID: https://orcid.org/0000-0002-9526-3043)
- Zhipeng Quan (ORCID: https://orcid.org/0009-0002-7392-8785)
Institutions
- Shandong University of Science and Technology (CN)
Publication Details
- Journal
- Journal of Computer and Communications
- Published
- 2025-01-01
- DOI
- https://doi.org/10.4236/jcc.2025.136005
- Primary Topic
- Video Surveillance and Tracking Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00