Weilong Huang, Lizuo Jin, Yi Luo, Yawei Li, Tong Cui
{"title":"一种新的废弃物体检测算法","authors":"Weilong Huang, Lizuo Jin, Yi Luo, Yawei Li, Tong Cui","doi":"10.1109/ICINFA.2016.7832071","DOIUrl":null,"url":null,"abstract":"Abandoned object detection is a crucial problem in many computer vision tasks. Traditional method based on foreground/background extraction techniques leads to a high false alarm rate. In this paper, we propose a novel detection algorithm based on change detection and blob separation. Our proposed approach suits more practical scenarios in which objects located near each other. Experiments are conducted on several well-known benchmarks to validate the efficacy of the algorithm proposed in this paper.","PeriodicalId":389619,"journal":{"name":"2016 IEEE International Conference on Information and Automation (ICIA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A novel algorithm for abandoned object detection\",\"authors\":\"Weilong Huang, Lizuo Jin, Yi Luo, Yawei Li, Tong Cui\",\"doi\":\"10.1109/ICINFA.2016.7832071\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abandoned object detection is a crucial problem in many computer vision tasks. Traditional method based on foreground/background extraction techniques leads to a high false alarm rate. In this paper, we propose a novel detection algorithm based on change detection and blob separation. Our proposed approach suits more practical scenarios in which objects located near each other. Experiments are conducted on several well-known benchmarks to validate the efficacy of the algorithm proposed in this paper.\",\"PeriodicalId\":389619,\"journal\":{\"name\":\"2016 IEEE International Conference on Information and Automation (ICIA)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Information and Automation (ICIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICINFA.2016.7832071\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Information and Automation (ICIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICINFA.2016.7832071","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Abandoned object detection is a crucial problem in many computer vision tasks. Traditional method based on foreground/background extraction techniques leads to a high false alarm rate. In this paper, we propose a novel detection algorithm based on change detection and blob separation. Our proposed approach suits more practical scenarios in which objects located near each other. Experiments are conducted on several well-known benchmarks to validate the efficacy of the algorithm proposed in this paper.
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