{"title":"用于交通监控系统的自动虹膜补偿","authors":"R. Cucchiara, R. Melli, A. Prati","doi":"10.1109/ITSC.2005.1520161","DOIUrl":null,"url":null,"abstract":"This paper addresses auto-iris compensation. Auto-iris can be really troublesome for motion detection and tracking techniques based on background or frame differencing, since it can change quickly the average intensity of the current frame. To cope with this, we introduced a two-step auto-iris compensation approach in our traffic monitoring system. First, the auto-iris detection is based on the computation of the average of the luminance difference obtained by background suppression. Then, if an auto-iris is detected, the compensation phase is started. In this phase, the auto-iris' behaviour is empirically modelled and, thus, compensated. Experimental results demonstrate the accuracy of the proposed approach, with both quantitative measures and visual analysis.","PeriodicalId":153203,"journal":{"name":"Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005.","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Auto-iris compensation for traffic surveillance systems\",\"authors\":\"R. Cucchiara, R. Melli, A. Prati\",\"doi\":\"10.1109/ITSC.2005.1520161\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper addresses auto-iris compensation. Auto-iris can be really troublesome for motion detection and tracking techniques based on background or frame differencing, since it can change quickly the average intensity of the current frame. To cope with this, we introduced a two-step auto-iris compensation approach in our traffic monitoring system. First, the auto-iris detection is based on the computation of the average of the luminance difference obtained by background suppression. Then, if an auto-iris is detected, the compensation phase is started. In this phase, the auto-iris' behaviour is empirically modelled and, thus, compensated. Experimental results demonstrate the accuracy of the proposed approach, with both quantitative measures and visual analysis.\",\"PeriodicalId\":153203,\"journal\":{\"name\":\"Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005.\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITSC.2005.1520161\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2005.1520161","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Auto-iris compensation for traffic surveillance systems
This paper addresses auto-iris compensation. Auto-iris can be really troublesome for motion detection and tracking techniques based on background or frame differencing, since it can change quickly the average intensity of the current frame. To cope with this, we introduced a two-step auto-iris compensation approach in our traffic monitoring system. First, the auto-iris detection is based on the computation of the average of the luminance difference obtained by background suppression. Then, if an auto-iris is detected, the compensation phase is started. In this phase, the auto-iris' behaviour is empirically modelled and, thus, compensated. Experimental results demonstrate the accuracy of the proposed approach, with both quantitative measures and visual analysis.
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