{"title":"像素级算法在视频监控中的应用分析","authors":"L. D. Stefano, Giovanni Neri, Enrico Viarani","doi":"10.1109/ICIAP.2001.957066","DOIUrl":null,"url":null,"abstract":"We propose a classification for a set of pixel-level algorithms employed in video surveillance applications and define a performance evaluation metric, based on an analysis of experimental data, for comparing the addressed algorithms. The results of such a comparison are presented and discussed. The set of algorithms considered in this work includes several algorithms widely known in the literature.","PeriodicalId":365627,"journal":{"name":"Proceedings 11th International Conference on Image Analysis and Processing","volume":"2020 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Analysis of pixel-level algorithms for video surveillance applications\",\"authors\":\"L. D. Stefano, Giovanni Neri, Enrico Viarani\",\"doi\":\"10.1109/ICIAP.2001.957066\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a classification for a set of pixel-level algorithms employed in video surveillance applications and define a performance evaluation metric, based on an analysis of experimental data, for comparing the addressed algorithms. The results of such a comparison are presented and discussed. The set of algorithms considered in this work includes several algorithms widely known in the literature.\",\"PeriodicalId\":365627,\"journal\":{\"name\":\"Proceedings 11th International Conference on Image Analysis and Processing\",\"volume\":\"2020 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 11th International Conference on Image Analysis and Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIAP.2001.957066\",\"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 11th International Conference on Image Analysis and Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIAP.2001.957066","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of pixel-level algorithms for video surveillance applications
We propose a classification for a set of pixel-level algorithms employed in video surveillance applications and define a performance evaluation metric, based on an analysis of experimental data, for comparing the addressed algorithms. The results of such a comparison are presented and discussed. The set of algorithms considered in this work includes several algorithms widely known in the literature.
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