{"title":"一种快速鲁棒的视频监控人员计数方法","authors":"Enwei Zhang, Feng Chen","doi":"10.1109/CIS.2007.85","DOIUrl":null,"url":null,"abstract":"Video surveillance has become more and more prevalent. It is a basic problem to get the number of access people in scenes. When occlusions occur, it becomes difficult to count people. We propose a fast and robust people counting method, and implement a system. In our system, we use group tracking to compensate weakness of multiple human segmentation, which can handle complete occlusion. Our system can run in real-time about 30fps for CIF video, with counting accuracy defined by frame above 95%.","PeriodicalId":127238,"journal":{"name":"2007 International Conference on Computational Intelligence and Security (CIS 2007)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"38","resultStr":"{\"title\":\"A Fast and Robust People Counting Method in Video Surveillance\",\"authors\":\"Enwei Zhang, Feng Chen\",\"doi\":\"10.1109/CIS.2007.85\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Video surveillance has become more and more prevalent. It is a basic problem to get the number of access people in scenes. When occlusions occur, it becomes difficult to count people. We propose a fast and robust people counting method, and implement a system. In our system, we use group tracking to compensate weakness of multiple human segmentation, which can handle complete occlusion. Our system can run in real-time about 30fps for CIF video, with counting accuracy defined by frame above 95%.\",\"PeriodicalId\":127238,\"journal\":{\"name\":\"2007 International Conference on Computational Intelligence and Security (CIS 2007)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"38\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Conference on Computational Intelligence and Security (CIS 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIS.2007.85\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Computational Intelligence and Security (CIS 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS.2007.85","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Fast and Robust People Counting Method in Video Surveillance
Video surveillance has become more and more prevalent. It is a basic problem to get the number of access people in scenes. When occlusions occur, it becomes difficult to count people. We propose a fast and robust people counting method, and implement a system. In our system, we use group tracking to compensate weakness of multiple human segmentation, which can handle complete occlusion. Our system can run in real-time about 30fps for CIF video, with counting accuracy defined by frame above 95%.
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