Tangent Sampson Error: Fast Approximate Two-view Reprojection Error for Central Camera Models
Mikhail Terekhov, Viktor Larsson
摘要
In this paper we introduce the Tangent Sampson error, which is a generalization of the classical Sampson error in two-view geometry that allows for arbitrary central camera models. It only requires local gradients of the distortion map at the original correspondences (allowing for pre-computation) resulting in a negligible increase in computational cost when used in RANSAC or local refinement. The error effectively approximates the true-reprojection error for a large variety of cameras, including extremely wide field-of-view lenses that cannot be undistorted to a single pinhole image. We show experimentally that the new error outperforms competing approaches both when used for model scoring in RANSAC and for non-linear refinement of the relative camera pose.
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- Revisiting Sampson Approximations for Geometric Estimation ProblemsFelix Rydell, Angélica Torres, Viktor LarssonCVPR 2024 · 被引用 2 次
- Visual Sync: Multi-Camera Synchronization via Cross-View Object MotionShaowei Liu, David Yifan Yao, Saurabh Gupta, Shenlong WangNeurIPS 2025 · 被引用 1 次
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