Clemens Arth, Manfred Klopschitz, Gerhard Reitmayr, D. Schmalstieg
{"title":"Real-time self-localization from panoramic images on mobile devices","authors":"Clemens Arth, Manfred Klopschitz, Gerhard Reitmayr, D. Schmalstieg","doi":"10.1109/ISMAR.2011.6092368","DOIUrl":null,"url":null,"abstract":"Self-localization in large environments is a vital task for accurately registered information visualization in outdoor Augmented Reality (AR) applications. In this work, we present a system for self-localization on mobile phones using a GPS prior and an online-generated panoramic view of the user's environment. The approach is suitable for executing entirely on current generation mobile devices, such as smartphones. Parallel execution of online incremental panorama generation and accurate 6DOF pose estimation using 3D point reconstructions allows for real-time self-localization and registration in large-scale environments. The power of our approach is demonstrated in several experimental evaluations.","PeriodicalId":298757,"journal":{"name":"2011 10th IEEE International Symposium on Mixed and Augmented Reality","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"97","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 10th IEEE International Symposium on Mixed and Augmented Reality","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISMAR.2011.6092368","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 97
Abstract
Self-localization in large environments is a vital task for accurately registered information visualization in outdoor Augmented Reality (AR) applications. In this work, we present a system for self-localization on mobile phones using a GPS prior and an online-generated panoramic view of the user's environment. The approach is suitable for executing entirely on current generation mobile devices, such as smartphones. Parallel execution of online incremental panorama generation and accurate 6DOF pose estimation using 3D point reconstructions allows for real-time self-localization and registration in large-scale environments. The power of our approach is demonstrated in several experimental evaluations.