Sphere Localization from a Minimal Number of Points in a Single Image

Kunfeng Shi, Xuebin Li, Huikun Xu, Hongmei Zhao, Huanlong Zhang

2019

Abstract

This paper proposes a new three-point method to locate the spatial sphere center from a single image. In monocular vision system with known intrinsic parameters, the traditional methods of locating the center of a spatial sphere with known radius require fitting its image points to an ellipse from which the sphere center is extracted. The ellipse fitting procedure requires at least five image points whereas the projection ellipse of a sphere essentially is a three-degree-of-freedom problem, which implies that over-parametrization is introduced in ellipse fitting. In this paper, the ellipse is represented with the three coordinates of the sphere center, and then at least three image points on the ellipse are used to construct a set of quadratic equations of the coordinates from which the Gro ̈bner basis method is used to solve for the coordinates. The experimental results show that the three-point method can solve the problem with less than five image points, and when the number of image points increases to five or more, the new method can also improve sphere localization accuracy and have improved robustness.

Paper Citation

in Harvard Style

Shi K., Li X., Xu H., Zhao H. and Zhang H. (2019). Sphere Localization from a Minimal Number of Points in a Single Image.In Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - Volume 1: CTISC, ISBN 978-989-758-357-5, pages 65-70. DOI: 10.5220/0008096300650070

in Bibtex Style

@conference{ctisc19,
author={Kunfeng Shi and Xuebin Li and Huikun Xu and Hongmei Zhao and Huanlong Zhang},
title={Sphere Localization from a Minimal Number of Points in a Single Image},
booktitle={Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - Volume 1: CTISC,},
year={2019},
pages={65-70},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008096300650070},
isbn={978-989-758-357-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - Volume 1: CTISC,
TI - Sphere Localization from a Minimal Number of Points in a Single Image
SN - 978-989-758-357-5
AU - Shi K.
AU - Li X.
AU - Xu H.
AU - Zhao H.
AU - Zhang H.
PY - 2019
SP - 65
EP - 70
DO - 10.5220/0008096300650070