{"title":"九头蛇:使用剪影检测和跟踪多人","authors":"I. Haritaoglu, D. Harwood, L. Davis","doi":"10.1109/VS.1999.780263","DOIUrl":null,"url":null,"abstract":"Hydra, is a real-time system for detecting and tracking multiple people when they appear in a group. We describe the computational models employed by Hydra to track multiple people before, during and after occlusion. Hydra combines a silhouette-based shape model, a motion model, and correlation-based matching methods to classify whether or not a foreground region contains multiple people, and to segment the region into its constituent people and track them. Experimental results demonstrate robustness and real-time performance of the algorithm.","PeriodicalId":371192,"journal":{"name":"Proceedings Second IEEE Workshop on Visual Surveillance (VS'99) (Cat. No.98-89223)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Hydra: multiple people detection and tracking using silhouettes\",\"authors\":\"I. Haritaoglu, D. Harwood, L. Davis\",\"doi\":\"10.1109/VS.1999.780263\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hydra, is a real-time system for detecting and tracking multiple people when they appear in a group. We describe the computational models employed by Hydra to track multiple people before, during and after occlusion. Hydra combines a silhouette-based shape model, a motion model, and correlation-based matching methods to classify whether or not a foreground region contains multiple people, and to segment the region into its constituent people and track them. Experimental results demonstrate robustness and real-time performance of the algorithm.\",\"PeriodicalId\":371192,\"journal\":{\"name\":\"Proceedings Second IEEE Workshop on Visual Surveillance (VS'99) (Cat. No.98-89223)\",\"volume\":\"121 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Second IEEE Workshop on Visual Surveillance (VS'99) (Cat. No.98-89223)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VS.1999.780263\",\"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 Second IEEE Workshop on Visual Surveillance (VS'99) (Cat. No.98-89223)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VS.1999.780263","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hydra: multiple people detection and tracking using silhouettes
Hydra, is a real-time system for detecting and tracking multiple people when they appear in a group. We describe the computational models employed by Hydra to track multiple people before, during and after occlusion. Hydra combines a silhouette-based shape model, a motion model, and correlation-based matching methods to classify whether or not a foreground region contains multiple people, and to segment the region into its constituent people and track them. Experimental results demonstrate robustness and real-time performance of the algorithm.