{"title":"Structured Light Field Design for Correspondence Free Rotation Estimation","authors":"Ian Schillebeeckx, Robert Pless","doi":"10.1109/ICCPHOT.2015.7168376","DOIUrl":null,"url":null,"abstract":"Many vision and augmented reality applications require knowing the rotation of the camera relative to an object or scene. In this paper we propose to create a structured light field designed explicitly to simplify the estimation of camera rotation. The light field is created using a lenticular sheet with a color coded backplane pattern, creating a light field where the observed color depends on the direction of the light. We show that a picture taken within such a light field gives linear constraints on the K-1R matrix that defines the camera calibration and rotation. In this work we derive an optimization that uses these constraints to rapidly estimate rotation, demonstrate a physical prototype and characterize its sensitivity to errors in the camera focal length and camera color sensitivity.","PeriodicalId":302766,"journal":{"name":"2015 IEEE International Conference on Computational Photography (ICCP)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Computational Photography (ICCP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCPHOT.2015.7168376","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Many vision and augmented reality applications require knowing the rotation of the camera relative to an object or scene. In this paper we propose to create a structured light field designed explicitly to simplify the estimation of camera rotation. The light field is created using a lenticular sheet with a color coded backplane pattern, creating a light field where the observed color depends on the direction of the light. We show that a picture taken within such a light field gives linear constraints on the K-1R matrix that defines the camera calibration and rotation. In this work we derive an optimization that uses these constraints to rapidly estimate rotation, demonstrate a physical prototype and characterize its sensitivity to errors in the camera focal length and camera color sensitivity.