{"title":"因子图在多相机海上跟踪融合中的应用","authors":"F. Castaldo, F. Palmieri","doi":"10.1109/CIP.2014.6844515","DOIUrl":null,"url":null,"abstract":"Propagation of Gaussian belief messages in factor graphs in normal form is applied to data fusion for tracking moving objects in maritime scenarios, as crowded harbors. The data are yielded by multiple cameras, deployed in the region under surveillance, and AIS system, wherever is available. The track model and the estimates coming from the sensors are integrated bi-directionally, providing a flexible framework for comprehensive inference. The framework is applied to tracking a large cargo ship in a harbor from frames recorded with three commercial cameras.","PeriodicalId":117669,"journal":{"name":"2014 4th International Workshop on Cognitive Information Processing (CIP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Application of factor graphs to multi-camera fusion for maritime tracking\",\"authors\":\"F. Castaldo, F. Palmieri\",\"doi\":\"10.1109/CIP.2014.6844515\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Propagation of Gaussian belief messages in factor graphs in normal form is applied to data fusion for tracking moving objects in maritime scenarios, as crowded harbors. The data are yielded by multiple cameras, deployed in the region under surveillance, and AIS system, wherever is available. The track model and the estimates coming from the sensors are integrated bi-directionally, providing a flexible framework for comprehensive inference. The framework is applied to tracking a large cargo ship in a harbor from frames recorded with three commercial cameras.\",\"PeriodicalId\":117669,\"journal\":{\"name\":\"2014 4th International Workshop on Cognitive Information Processing (CIP)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 4th International Workshop on Cognitive Information Processing (CIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIP.2014.6844515\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 4th International Workshop on Cognitive Information Processing (CIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIP.2014.6844515","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of factor graphs to multi-camera fusion for maritime tracking
Propagation of Gaussian belief messages in factor graphs in normal form is applied to data fusion for tracking moving objects in maritime scenarios, as crowded harbors. The data are yielded by multiple cameras, deployed in the region under surveillance, and AIS system, wherever is available. The track model and the estimates coming from the sensors are integrated bi-directionally, providing a flexible framework for comprehensive inference. The framework is applied to tracking a large cargo ship in a harbor from frames recorded with three commercial cameras.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
