{"title":"透过闭路电视侦测回收中心的非法倾倒物料","authors":"N. Harte, A. Rankin, G. Baugh, A. Kokaram","doi":"10.1109/IMVIP.2007.17","DOIUrl":null,"url":null,"abstract":"This paper describes initial work on a framework for automatic detection of illegal dumping from CCTV footage from recycle centres. Frames are seperated into foreground and background regions using a Bayesian approach that combines global motion estimates with image based information to generate a robust segmentation. The framework hence avoids explicit modelling and tracking of objects in the scene such as cars, people or rubbish bags. A feature extraction stage with diagnostics will be presented.","PeriodicalId":249544,"journal":{"name":"International Machine Vision and Image Processing Conference (IMVIP 2007)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Detection of Illegal Dumping from CCTV at Recycling Centres\",\"authors\":\"N. Harte, A. Rankin, G. Baugh, A. Kokaram\",\"doi\":\"10.1109/IMVIP.2007.17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes initial work on a framework for automatic detection of illegal dumping from CCTV footage from recycle centres. Frames are seperated into foreground and background regions using a Bayesian approach that combines global motion estimates with image based information to generate a robust segmentation. The framework hence avoids explicit modelling and tracking of objects in the scene such as cars, people or rubbish bags. A feature extraction stage with diagnostics will be presented.\",\"PeriodicalId\":249544,\"journal\":{\"name\":\"International Machine Vision and Image Processing Conference (IMVIP 2007)\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Machine Vision and Image Processing Conference (IMVIP 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMVIP.2007.17\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Machine Vision and Image Processing Conference (IMVIP 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMVIP.2007.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection of Illegal Dumping from CCTV at Recycling Centres
This paper describes initial work on a framework for automatic detection of illegal dumping from CCTV footage from recycle centres. Frames are seperated into foreground and background regions using a Bayesian approach that combines global motion estimates with image based information to generate a robust segmentation. The framework hence avoids explicit modelling and tracking of objects in the scene such as cars, people or rubbish bags. A feature extraction stage with diagnostics will be presented.