{"title":"Cooperative estimation of 3D target object motion via networked visual motion observers","authors":"T. Hatanaka, K. Hirata, M. Fujita","doi":"10.1109/CDC.2011.6160515","DOIUrl":null,"url":null,"abstract":"This paper addresses cooperative estimation of 3D target motion for visual sensor networks. In one of our previous works, we already presented a cooperative estimation algorithm called networked visual motion observers. In this paper, we first clarify averaging accuracy attained by the networked estimation mechanism. Then, we analyze convergence speed of the estimates and clarify a relation of the speed to the graph structures. Moreover, we also reveal a tracking performance of the estimates to target objects motion and derive a connection between the tracking performance and a visual feedback gain in the algorithm. Finally the effectiveness of the present estimation algorithm is demonstrated through experiments.","PeriodicalId":360068,"journal":{"name":"IEEE Conference on Decision and Control and European Control Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Conference on Decision and Control and European Control Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.2011.6160515","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This paper addresses cooperative estimation of 3D target motion for visual sensor networks. In one of our previous works, we already presented a cooperative estimation algorithm called networked visual motion observers. In this paper, we first clarify averaging accuracy attained by the networked estimation mechanism. Then, we analyze convergence speed of the estimates and clarify a relation of the speed to the graph structures. Moreover, we also reveal a tracking performance of the estimates to target objects motion and derive a connection between the tracking performance and a visual feedback gain in the algorithm. Finally the effectiveness of the present estimation algorithm is demonstrated through experiments.