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• W3125514181 endingPage "1056" @default.
• W3125514181 startingPage "1036" @default.
• W3125514181 abstract "This work contributes an efficient algorithm to compute the Relative Pose problem (RPp) between calibrated cameras and certify the optimality of the solution, given a set of pair-wise feature correspondences affected by noise and probably corrupted by wrong matches. We propose a family of certifiers that is shown to increase the ratio of detected optimal solutions. This set of certifiers is incorporated into a fast essential matrix estimation pipeline that, given any initial guess for the RPp, refines it iteratively on the product space of 3D rotations and 2-sphere. In addition, this fast certifiable pipeline is integrated into a robust framework that combines Graduated Non-convexity and the Black-Rangarajan duality between robust functions and line processes. We proved through extensive experiments on synthetic and real data that the proposed framework provides a fast and robust relative pose estimation. We make the code publicly available url{https://github.com/mergarsal/FastCertRelPose.git}." @default.
• W3125514181 created "2021-02-01" @default.
• W3125514181 creator A5070626607 @default.
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• W3125514181 date "2021-06-22" @default.
• W3125514181 modified "2023-10-02" @default.
• W3125514181 title "Fast and Robust Certifiable Estimation of the Relative Pose Between Two Calibrated Cameras" @default.
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• W3125514181 doi "https://doi.org/10.1007/s10851-021-01044-0" @default.
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