R. Peng, R. Sclabassi, Q. Liu, Bing Liu, J. Xu, M. Sun
{"title":"Object-Based Video Representation for Remote Patient Monitoring","authors":"R. Peng, R. Sclabassi, Q. Liu, Bing Liu, J. Xu, M. Sun","doi":"10.1109/DDHH.2006.1624803","DOIUrl":null,"url":null,"abstract":"Object-based video representation plays an important role in remote patient monitoring built on video coding and Internet transmission. This paper introduces an object-based video representation method using two novel change detection techniques, and presents a demo system built upon ConferenceXP, where three types of video objects are constructed by exploiting the features in patient monitoring video. Our experimental results based on real-world data have shown that these techniques provide better foreground and background separation, higher coding efficiency, and improved performance in remote patient monitoring","PeriodicalId":164569,"journal":{"name":"1st Transdisciplinary Conference on Distributed Diagnosis and Home Healthcare, 2006. D2H2.","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1st Transdisciplinary Conference on Distributed Diagnosis and Home Healthcare, 2006. D2H2.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DDHH.2006.1624803","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Object-based video representation plays an important role in remote patient monitoring built on video coding and Internet transmission. This paper introduces an object-based video representation method using two novel change detection techniques, and presents a demo system built upon ConferenceXP, where three types of video objects are constructed by exploiting the features in patient monitoring video. Our experimental results based on real-world data have shown that these techniques provide better foreground and background separation, higher coding efficiency, and improved performance in remote patient monitoring