Extrinsic Camera Calibration with Minimal Configuration Using Cornea Model and Equidistance Constraint

Q1 Computer Science
Kosuke Takahashi, Dan Mikami, Mariko Isogawa, Akira Kojima
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引用次数: 3

Abstract

In this paper, we propose a novel algorithm to extrinsically calibrate a camera to a 3D reference object that is not directly visible from the camera. We use the spherical human cornea as a mirror and calibrate the extrinsic parameters from its reflection of the reference points. The key contribution of this paper is to present a cornea-reflectionbased calibration algorithm with minimal configuration; there are three reference points and one mirror pose. The proposed algorithm introduces two constraints. First constraint is that the cornea is virtually a sphere, which enables us to estimate the center of the cornea sphere from its projection. Second is the equidistance constraint, which enables us to estimate the 3D position of the reference point by assuming that the center of the camera and reference point are located the same distance from the center of the cornea sphere. We demonstrate the advantages of the proposed method with qualitative and quantitative evaluations using synthesized and real data.
基于角膜模型和等距约束的最小配置摄像机外部标定
在本文中,我们提出了一种新的算法来外部校准相机到一个三维参考对象,这是不直接从相机可见。我们利用人的球形角膜作为镜子,从它对参考点的反射来校准外部参数。本文的主要贡献是提出了一种基于最小配置的角膜反射校准算法;有三个参考点和一个镜像姿势。该算法引入了两个约束条件。第一个限制是角膜实际上是一个球体,这使我们能够从角膜球体的投影来估计它的中心。二是等距离约束,即假设相机中心和参考点距离角膜球中心的距离相同,从而估计参考点的三维位置。通过综合数据和真实数据的定性和定量评价,证明了该方法的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IPSJ Transactions on Computer Vision and Applications
IPSJ Transactions on Computer Vision and Applications Computer Science-Computer Vision and Pattern Recognition
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