Tangent Sampson Error: Fast Approximate Two-view Reprojection Error for Central Camera Models

Mikhail Terekhov, Viktor Larsson; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023, pp. 3370-3378

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.