{"title":"Robust focal length estimation based on minimal solution method","authors":"Deqing Chen, Hang Shao, Qionghai Dai","doi":"10.1109/3DTV.2011.5877179","DOIUrl":null,"url":null,"abstract":"We present a new approach to estimate the focal length for camera calibration in multiview reconstruction. As a popular camera calibration approach, minimal solution method gives rise to a great number of focal-length estimates, from which generating an accurate one is of great significance. Our method concentrates on how to obtain an accurate estimate and is carried out in two steps: firstly, a norm constraint for the fundamental matrix is employed to prune the low-confidence focal-length candidates. Then the focal-length estimate is obtained with a robust focal-length estimation scheme, which consists of occurrence to probability transform, focal-length candidates resample and final estimation with expectation. Experimental results demonstrate that our method could obtain better estimate with both higher accuracy and higher stability than the state-of-the-art method.","PeriodicalId":158764,"journal":{"name":"2011 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/3DTV.2011.5877179","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We present a new approach to estimate the focal length for camera calibration in multiview reconstruction. As a popular camera calibration approach, minimal solution method gives rise to a great number of focal-length estimates, from which generating an accurate one is of great significance. Our method concentrates on how to obtain an accurate estimate and is carried out in two steps: firstly, a norm constraint for the fundamental matrix is employed to prune the low-confidence focal-length candidates. Then the focal-length estimate is obtained with a robust focal-length estimation scheme, which consists of occurrence to probability transform, focal-length candidates resample and final estimation with expectation. Experimental results demonstrate that our method could obtain better estimate with both higher accuracy and higher stability than the state-of-the-art method.