Semantic-Based Deep Learning Algorithm for Vehicle Re-identification
Pages 363 - 367
Abstract
Re-identification of vehicles is very important in traffic safety, intelligent transportation, and smart cities. The traditional method of identifying vehicles is through license number. However, in some cases, the license number may be blocked, damaged, or fake. In this case, re-identification of vehicles is a difficult challenge without license number. In this article, we propose a vehicle re-identification method based on vehicle semantic information and deep learning. First, extract the overall feature value of the vehicle and use it to identify vehicles with different shapes. Secondly, the semantic information of the vehicle image is perceived, and the characteristic value of the vehicle semantic information is extracted based on the above results, which is used to identify vehicles with the same or similar appearance. Then the overall feature value of the vehicle image and the feature value of semantic information are fused into a comprehensive feature value. Use the generated feature value to calculate the distance to the feature value of other vehicle images, and re-identify massive vehicle images. Finally, we conducted verification on two different data sets. The experimental results show that the proposed algorithm is capable of producing better results.
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- Semantic-Based Deep Learning Algorithm for Vehicle Re-identification
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Published In
March 2022
809 pages
ISBN:9781450396110
DOI:10.1145/3532213
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 13 July 2022
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- Research-article
- Research
- Refereed limited
Funding Sources
- the Opening Project of Key Laboratory of operation safety technology on transport vehicles ?Ministry of Transport, PRC
Conference
ICCAI '22
ICCAI '22: 2022 8th International Conference on Computing and Artificial Intelligence
March 18 - 21, 2022
Tianjin, China
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