Automatic Camera Calibration with Structure and Motion Recovery from Two Views of a Polyhedral Structure

Flavio Vigueras, Mario Santés, J. Hayet
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引用次数: 1

Abstract

This work addresses the problems of (i) self-calibration of a moving camera observing a 3D scene composed by planar structures and (ii) scene segmentation and reconstruction. Although there exist some works intending to deal with these problems, most of them are based on the estimation of the epipolar geometry, non-linear optimization, or linear systems that do not incorporate geometrical consistency and may produce undesirable side-effects. In this paper, we propose a novel iterative linear algorithm that exploits the geometrical and algebraic constraints induced by rigidity and planarity in the scene. Instead of solving a complex multi-linear problem, we solve iteratively several linear problems: coplanar features segmentation, planar projective transferring, epipole computation, and all the plane intersections. Linear methods allow our approach to be suitable for real-time localization and 3D reconstruction, e.g. for autonomous mobile robots applications. Furthermore, we avoid the explicit epipolar geometry computation and all the stability problems commonly associated with it.
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基于多面体结构两视角的结构和运动恢复的相机自动标定
这项工作解决了(i)观察由平面结构组成的3D场景的移动摄像机的自校准问题和(ii)场景分割和重建问题。虽然已有一些研究试图解决这些问题,但大多数都是基于极极几何的估计、非线性优化或线性系统,这些系统不包含几何一致性,可能产生不良的副作用。在本文中,我们提出了一种新的迭代线性算法,该算法利用了场景中由刚性和平面性引起的几何和代数约束。我们不是解决复杂的多线性问题,而是迭代地解决几个线性问题:共面特征分割、平面投影传递、极点计算和所有平面相交。线性方法使我们的方法适用于实时定位和3D重建,例如自主移动机器人应用。此外,我们避免了显式的极几何计算和所有通常与之相关的稳定性问题。
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