Vehicle re-identification system for road side unit application

Xiu-Zhi Chen; Chi Peng; Mu-Chuan Li; Yen-Lin Chen

doi:10.1117/12.2626089

30 April 2022 Vehicle re-identification system for road side unit application

Xiu-Zhi Chen, Chi Peng, Mu-Chuan Li, Yen-Lin Chen

Proceedings Volume 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022; 121770X (2022) https://doi.org/10.1117/12.2626089
Event: International Workshop on Advanced Imaging Technology 2022 (IWAIT 2022), 2022, Hong Kong, China

Abstract

Vehicle re-identification is one of the complex smart traffic issues, due to the large intra-class variation and high interclass similarity, it is hard to be solved through traditional hand-crafted features. In this paper, we proposed a vehicle re-identification system based on deep learning techniques, which is able to re-identify the vehicles through deep features under acceptable operation time on Nvidia Jetson TX2. We have collected multiple sequences captured from real-world road side units (RSU) for system evaluation experiments, and the results indicate that it is highly possible to be adopted for real world traffic applications.

Citation Download Citation

Xiu-Zhi Chen, Chi Peng, Mu-Chuan Li, and Yen-Lin Chen "Vehicle re-identification system for road side unit application", Proc. SPIE 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022, 121770X (30 April 2022); https://doi.org/10.1117/12.2626089

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