{"title":"视频序列中的人群检测","authors":"Pini. Reisman Ofer, Mano Shai, Avidan Amnon","doi":"10.1109/IVS.2004.1336357","DOIUrl":null,"url":null,"abstract":"We present a real-time system that detects moving crowd in a video sequence. Crowd detection differs from pedestrian detection in that we assume that no individual pedestrian can be properly segmented in the image. We propose a scheme that looks at the motion patterns of crowd in the spatio-temporal domain and give an efficient implementation that can detect crowd in real-time. In our experiments we detected crowd at distances of up to 70 m.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"84","resultStr":"{\"title\":\"Crowd detection in video sequences\",\"authors\":\"Pini. Reisman Ofer, Mano Shai, Avidan Amnon\",\"doi\":\"10.1109/IVS.2004.1336357\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a real-time system that detects moving crowd in a video sequence. Crowd detection differs from pedestrian detection in that we assume that no individual pedestrian can be properly segmented in the image. We propose a scheme that looks at the motion patterns of crowd in the spatio-temporal domain and give an efficient implementation that can detect crowd in real-time. In our experiments we detected crowd at distances of up to 70 m.\",\"PeriodicalId\":296386,\"journal\":{\"name\":\"IEEE Intelligent Vehicles Symposium, 2004\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"84\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Intelligent Vehicles Symposium, 2004\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IVS.2004.1336357\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Intelligent Vehicles Symposium, 2004","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2004.1336357","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We present a real-time system that detects moving crowd in a video sequence. Crowd detection differs from pedestrian detection in that we assume that no individual pedestrian can be properly segmented in the image. We propose a scheme that looks at the motion patterns of crowd in the spatio-temporal domain and give an efficient implementation that can detect crowd in real-time. In our experiments we detected crowd at distances of up to 70 m.
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