RANSAC based three points algorithm for ellipse fitting of spherical object's projection

TL;DR

This paper introduces a novel three-point ellipse fitting algorithm for spherical object projections, utilizing RANSAC to improve robustness against noise, and significantly reducing the number of points needed compared to traditional methods.

Contribution

The paper presents a new three-point ellipse fitting method for spherical projections, differing from traditional five-point algorithms, and incorporates RANSAC for noise robustness.

Findings

Requires only three points for ellipse fitting

Uses RANSAC to handle noisy data effectively

Reduces computational complexity compared to traditional methods

Abstract

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.