{"title":"A Deflation based Fast and Robust Preconditioner for Bundle Adjustment","authors":"Shrutimoy Das, Siddhant Katyan, Pawan Kumar","doi":"10.1109/WACV48630.2021.00182","DOIUrl":null,"url":null,"abstract":"The bundle adjustment (BA) problem is formulated as a non linear least squares problem which, requires the solution of a linear system. For solving this system, we present the design and implementation of a fast preconditioned solver. The proposed preconditioner is based on the deflation of the largest eigenvalues of the Hessian. We also derive an estimate of the condition number of the preconditioned system. Numerical experiments on problems from the BAL dataset [3] suggest that our solver is the fastest, sometimes, by a factor of five, when compared to the current state-of-the-art solvers for bundle adjustment.","PeriodicalId":236300,"journal":{"name":"2021 IEEE Winter Conference on Applications of Computer Vision (WACV)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Winter Conference on Applications of Computer Vision (WACV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WACV48630.2021.00182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
The bundle adjustment (BA) problem is formulated as a non linear least squares problem which, requires the solution of a linear system. For solving this system, we present the design and implementation of a fast preconditioned solver. The proposed preconditioner is based on the deflation of the largest eigenvalues of the Hessian. We also derive an estimate of the condition number of the preconditioned system. Numerical experiments on problems from the BAL dataset [3] suggest that our solver is the fastest, sometimes, by a factor of five, when compared to the current state-of-the-art solvers for bundle adjustment.