{"title":"Hydra: multiple people detection and tracking using silhouettes","authors":"I. Haritaoglu, D. Harwood, L. Davis","doi":"10.1109/VS.1999.780263","DOIUrl":"https://doi.org/10.1109/VS.1999.780263","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":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133033742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}