RANSAC based three points algorithm for ellipse fitting of spherical object's projection
This addresses a specific computer vision problem for 3D reconstruction applications, representing an incremental improvement in ellipse fitting efficiency.
The paper tackles the problem of accurately fitting ellipses to spherical object projections for 3D reconstruction, proposing a method that requires only three points instead of the traditional five and achieves robust performance using RANSAC to handle noise.
As the spherical object can be seen everywhere, we should extract the ellipse image accurately and fit it by implicit algebraic curve in order to finish the 3D reconstruction. In this paper, we propose a new ellipse fitting algorithm which only needs three points to fit the projection of spherical object and is different from the traditional algorithms that need at least five point. The fitting procedure is just similar as the estimation of Fundamental Matrix estimation by seven points, and the RANSAC algorithm has also been used to exclude the interference of noise and scattered points.