Fengjiao Gao, Yumo Zhang, Tongjun Liu, Changjiang Song
{"title":"A vehicle re-identification method based on random occlusion","authors":"Fengjiao Gao, Yumo Zhang, Tongjun Liu, Changjiang Song","doi":"10.1117/12.2685756","DOIUrl":null,"url":null,"abstract":"In the computer vision field, vehicle re-identification research is an important direction. There have been many researchers doing research on vehicle re-identification. But they mostly focus on the overall image and ignore occluded images, which may be more practical and challenging. This paper proposed a re-identification method to solve the occlusion in remote sensing image, which extracted the pixels in the random rectangular area of the image and covers them to other positions of the image. The feasibility of the proposed random occlusion method was proved by experiments on simulated occlusion images. And experiments on real occlusion image data sets showed that the proposed random occlusion method was better than the random erasure method in solving the occlusion problem, and can obtain better re-identification results.","PeriodicalId":305812,"journal":{"name":"International Conference on Electronic Information Technology","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Electronic Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2685756","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In the computer vision field, vehicle re-identification research is an important direction. There have been many researchers doing research on vehicle re-identification. But they mostly focus on the overall image and ignore occluded images, which may be more practical and challenging. This paper proposed a re-identification method to solve the occlusion in remote sensing image, which extracted the pixels in the random rectangular area of the image and covers them to other positions of the image. The feasibility of the proposed random occlusion method was proved by experiments on simulated occlusion images. And experiments on real occlusion image data sets showed that the proposed random occlusion method was better than the random erasure method in solving the occlusion problem, and can obtain better re-identification results.