Smart City Gnosys

Smart city article details

Title	A Supervised Method Base On Multi Labels For Vehicle Re-Identification
ID_Doc	5110
Authors	Zhu J.; Deng S.; Chen D.
Year	2023
Published	Proceedings of SPIE - The International Society for Optical Engineering, 12636
DOI	http://dx.doi.org/10.1117/12.2675214
Abstract	With the rise of smart city construction, the importance of vehicle re-identification based on video surveillance has become increasingly prominent. The task of vehicle re-identification mainly focuses on recognizing the same vehicle image under different cameras. In this paper, we propose a multi-label fusion framework for vehicle re-identification based on VIT network. We design a method of anti-angle distortion data augmentation to solve the problem that the performance of VIT is limited by the relative position relationship inside the vehicle structure and the angle deviation caused by the different relative positions of camera and vehicle. At the same time, the key position weight information module is inserted into the coding layer to improve the network's attention to key information. Finally, in view of the insufficient use of the location information between patches in the VIT network, we design a location code based on the Minkowski distance metric to add the relative location relationships within the vehicle individuals to the network. The experiment shows that under the same conditions, our vehicle weight recognition system is superior to most of the more advanced work in vehicle-ID and VERI776 datasets compared with the most advanced supervised vehicle weight recognition work. © 2023 SPIE.
Author Keywords	Deep Learning; Multi Labels; Self-Attention Mechanism; Vehicle Re-identification; Visual Transformer

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