Re-ranking vehicle re-identification with orientation-guide query expansion
Vehicle re-identification, which aims to retrieve information regarding a vehicle from different cameras with non-overlapping views, has recently attracted extensive attention in the field of computer vision owing to the development of smart cities. This task can be regarded as a type of retrieval p...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi - SAGE Publishing
2022-03-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/15501477211066305 |
| _version_ | 1797766278530727936 |
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| author | Xue Zhang Xiushan Nie Ziruo Sun Xiaofeng Li Chuntao Wang Peng Tao Sumaira Hussain |
| author_facet | Xue Zhang Xiushan Nie Ziruo Sun Xiaofeng Li Chuntao Wang Peng Tao Sumaira Hussain |
| author_sort | Xue Zhang |
| collection | DOAJ |
| description | Vehicle re-identification, which aims to retrieve information regarding a vehicle from different cameras with non-overlapping views, has recently attracted extensive attention in the field of computer vision owing to the development of smart cities. This task can be regarded as a type of retrieval problem, where re-ranking is important for performance enhancement. In the vehicle re-identification ranking list, images whose orientations are dissimilar to that of the query image must preferably be optimized on priority. However, traditional methods are incompatible with such samples, resulting in unsatisfactory vehicle re-identification performances. Therefore, in this study, we propose a vehicle re-identification re-ranking method with orientation-guide query expansion to optimize the initial ranking list obtained by a re-identification model. In the proposed method, we first find the nearest neighbor image whose orientation is dissimilar to the queried image and then fuse the features of the query and neighbor images to obtain new features for information retrieval. Experiments are performed on two public data sets, VeRi-776 and VehicleID, and the effectiveness of the proposed method is confirmed. |
| first_indexed | 2024-03-12T20:21:57Z |
| format | Article |
| id | doaj.art-ee747594aa134edea365a99e8dbadc0f |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2024-03-12T20:21:57Z |
| publishDate | 2022-03-01 |
| publisher | Hindawi - SAGE Publishing |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-ee747594aa134edea365a99e8dbadc0f2023-08-02T00:51:45ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772022-03-011810.1177/15501477211066305Re-ranking vehicle re-identification with orientation-guide query expansionXue Zhang0Xiushan Nie1Ziruo Sun2Xiaofeng Li3Chuntao Wang4Peng Tao5Sumaira Hussain6School of Computer Science and Technology, Shandong Jianzhu University, Jinan, ChinaSchool of Computer Science and Technology, Shandong Jianzhu University, Jinan, ChinaSchool of Software, Shandong University, Jinan, ChinaSchool of Computer Science and Technology, Shandong Jianzhu University, Jinan, ChinaSNBC Ltd, Weihai, ChinaSNBC Ltd, Weihai, ChinaSindh Madressatul Islam University, Karachi, PakistanVehicle re-identification, which aims to retrieve information regarding a vehicle from different cameras with non-overlapping views, has recently attracted extensive attention in the field of computer vision owing to the development of smart cities. This task can be regarded as a type of retrieval problem, where re-ranking is important for performance enhancement. In the vehicle re-identification ranking list, images whose orientations are dissimilar to that of the query image must preferably be optimized on priority. However, traditional methods are incompatible with such samples, resulting in unsatisfactory vehicle re-identification performances. Therefore, in this study, we propose a vehicle re-identification re-ranking method with orientation-guide query expansion to optimize the initial ranking list obtained by a re-identification model. In the proposed method, we first find the nearest neighbor image whose orientation is dissimilar to the queried image and then fuse the features of the query and neighbor images to obtain new features for information retrieval. Experiments are performed on two public data sets, VeRi-776 and VehicleID, and the effectiveness of the proposed method is confirmed.https://doi.org/10.1177/15501477211066305 |
| spellingShingle | Xue Zhang Xiushan Nie Ziruo Sun Xiaofeng Li Chuntao Wang Peng Tao Sumaira Hussain Re-ranking vehicle re-identification with orientation-guide query expansion International Journal of Distributed Sensor Networks |
| title | Re-ranking vehicle re-identification with orientation-guide query expansion |
| title_full | Re-ranking vehicle re-identification with orientation-guide query expansion |
| title_fullStr | Re-ranking vehicle re-identification with orientation-guide query expansion |
| title_full_unstemmed | Re-ranking vehicle re-identification with orientation-guide query expansion |
| title_short | Re-ranking vehicle re-identification with orientation-guide query expansion |
| title_sort | re ranking vehicle re identification with orientation guide query expansion |
| url | https://doi.org/10.1177/15501477211066305 |
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