{"title":"用于混合现实的无标记实时摄像机配准","authors":"A. Liverani, Stefania Grandi","doi":"10.2312/LocalChapterEvents/ItalChap/ItalianChapConf2007/051-058","DOIUrl":null,"url":null,"abstract":"A real-time and robust algorithm for 3D camera registration in a Mixed Reality (MR) environment is described in this paper. The most used technique for camera pose (position and orientation with respect to a fixed or moving object) is based on fiducial marker tracking. This method guarantees good results in real-time with a single camera, but needs several high contrast printed markers on external world in order to make possible the calculation of camera parameters and positioning. Thus real 3D geometric data are grabbed only through already known markers. The aim of this research is a real-time monocular camera tracking and registration through automatic image features extraction from video streaming. The first implementation of the method, several examples and confrontation with non interactive algorithm for SFM (Structure From Motion) have demonstrated that this meets the real-time response and sufficient precision needed by a Mixed Reality environment.","PeriodicalId":405486,"journal":{"name":"European Interdisciplinary Cybersecurity Conference","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Marker-less Real-time Camera Registration for Mixed Reality\",\"authors\":\"A. Liverani, Stefania Grandi\",\"doi\":\"10.2312/LocalChapterEvents/ItalChap/ItalianChapConf2007/051-058\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A real-time and robust algorithm for 3D camera registration in a Mixed Reality (MR) environment is described in this paper. The most used technique for camera pose (position and orientation with respect to a fixed or moving object) is based on fiducial marker tracking. This method guarantees good results in real-time with a single camera, but needs several high contrast printed markers on external world in order to make possible the calculation of camera parameters and positioning. Thus real 3D geometric data are grabbed only through already known markers. The aim of this research is a real-time monocular camera tracking and registration through automatic image features extraction from video streaming. The first implementation of the method, several examples and confrontation with non interactive algorithm for SFM (Structure From Motion) have demonstrated that this meets the real-time response and sufficient precision needed by a Mixed Reality environment.\",\"PeriodicalId\":405486,\"journal\":{\"name\":\"European Interdisciplinary Cybersecurity Conference\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Interdisciplinary Cybersecurity Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2312/LocalChapterEvents/ItalChap/ItalianChapConf2007/051-058\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Interdisciplinary Cybersecurity Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2312/LocalChapterEvents/ItalChap/ItalianChapConf2007/051-058","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
本文提出了一种用于混合现实环境下三维摄像机配准的实时鲁棒算法。相机姿态(相对于固定或移动物体的位置和方向)最常用的技术是基于基准标记跟踪。该方法保证了单相机的实时性,但需要在外部世界上打印多个高对比度的标记,以便计算相机参数和定位。因此,真正的三维几何数据只能通过已知的标记来获取。本研究的目的是通过自动提取视频流中的图像特征,实现单目摄像机的实时跟踪与配准。该方法的首次实现、几个实例以及与非交互式SFM (Structure From Motion)算法的对抗表明,该方法满足了混合现实环境所需的实时响应和足够的精度。
Marker-less Real-time Camera Registration for Mixed Reality
A real-time and robust algorithm for 3D camera registration in a Mixed Reality (MR) environment is described in this paper. The most used technique for camera pose (position and orientation with respect to a fixed or moving object) is based on fiducial marker tracking. This method guarantees good results in real-time with a single camera, but needs several high contrast printed markers on external world in order to make possible the calculation of camera parameters and positioning. Thus real 3D geometric data are grabbed only through already known markers. The aim of this research is a real-time monocular camera tracking and registration through automatic image features extraction from video streaming. The first implementation of the method, several examples and confrontation with non interactive algorithm for SFM (Structure From Motion) have demonstrated that this meets the real-time response and sufficient precision needed by a Mixed Reality environment.