References & Citations
Computer Science > Computer Vision and Pattern Recognition
Title: From Correspondences to Pose: Non-minimal Certifiably Optimal Relative Pose without Disambiguation
(Submitted on 10 Dec 2023 (v1), last revised 27 Mar 2024 (this version, v2))
Abstract: Estimating the relative camera pose from $n \geq 5$ correspondences between two calibrated views is a fundamental task in computer vision. This process typically involves two stages: 1) estimating the essential matrix between the views, and 2) disambiguating among the four candidate relative poses that satisfy the epipolar geometry. In this paper, we demonstrate a novel approach that, for the first time, bypasses the second stage. Specifically, we show that it is possible to directly estimate the correct relative camera pose from correspondences without needing a post-processing step to enforce the cheirality constraint on the correspondences. Building on recent advances in certifiable non-minimal optimization, we frame the relative pose estimation as a Quadratically Constrained Quadratic Program (QCQP). By applying the appropriate constraints, we ensure the estimation of a camera pose that corresponds to a valid 3D geometry and that is globally optimal when certified. We validate our method through exhaustive synthetic and real-world experiments, confirming the efficacy, efficiency and accuracy of the proposed approach. Code is available at this https URL
Submission history
From: Javier Tirado-Garín [view email][v1] Sun, 10 Dec 2023 20:57:31 GMT (1944kb,D)
[v2] Wed, 27 Mar 2024 18:21:12 GMT (1709kb,D)
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