{"title":"近似最佳视觉传感器放置","authors":"E. Hörster, R. Lienhart","doi":"10.1109/ICME.2006.262766","DOIUrl":null,"url":null,"abstract":"Many novel multimedia applications use visual sensor arrays. In this paper we address the problem of optimally placing multiple visual sensors in a given space. Our linear programming approach determines the minimum number of cameras needed to cover the space completely at a given sampling frequency. Simultaneously it determines the optimal positions and poses of the visual sensors. We also show how to account for visual sensors with different properties and costs if more than one kind is available, and report performance results.","PeriodicalId":339258,"journal":{"name":"2006 IEEE International Conference on Multimedia and Expo","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"78","resultStr":"{\"title\":\"Approximating Optimal Visual Sensor Placement\",\"authors\":\"E. Hörster, R. Lienhart\",\"doi\":\"10.1109/ICME.2006.262766\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many novel multimedia applications use visual sensor arrays. In this paper we address the problem of optimally placing multiple visual sensors in a given space. Our linear programming approach determines the minimum number of cameras needed to cover the space completely at a given sampling frequency. Simultaneously it determines the optimal positions and poses of the visual sensors. We also show how to account for visual sensors with different properties and costs if more than one kind is available, and report performance results.\",\"PeriodicalId\":339258,\"journal\":{\"name\":\"2006 IEEE International Conference on Multimedia and Expo\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"78\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE International Conference on Multimedia and Expo\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICME.2006.262766\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE International Conference on Multimedia and Expo","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICME.2006.262766","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Many novel multimedia applications use visual sensor arrays. In this paper we address the problem of optimally placing multiple visual sensors in a given space. Our linear programming approach determines the minimum number of cameras needed to cover the space completely at a given sampling frequency. Simultaneously it determines the optimal positions and poses of the visual sensors. We also show how to account for visual sensors with different properties and costs if more than one kind is available, and report performance results.