线性多视图重建和相机恢复

C. Rother, S. Carlsson
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引用次数: 62

摘要

本文提出了一种基于参考平面上四个点在所有视图中可见的前提下,从多个视角同时计算三维点和摄像机位置的线性算法。通过使用奇异值分解找到矩阵的零空间,在一个步骤中实现了重建和相机恢复。与分解算法不同,本文提出的算法不要求所有点在所有视图中都可见。通过同时重建点和视图,利用了具有大互基线的大分布相机的数值稳定效果。给出了有限参考平面和无限参考平面的实验结果。该方法的一个特别有趣的应用是重建建筑场景,将参考平面作为通过三个正交消失点可见的无穷远处的平面。这是通过在一个单一的SVD中基于35个视图重建建筑物的外部和内部(庭院)来证明的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Linear multi view reconstruction and camera recovery
This paper presents a linear algorithm for the simultaneous computation of 3D points and camera positions from multiple perspective views, based on having four points on a reference plane visible in all views. The reconstruction and camera recovery is achieved, in a single step, by finding the null-space of a matrix using singular value decomposition. Unlike factorization algorithms, the presented algorithm does not require all points to be visible in all views. By simultaneously reconstructing points and views the numerically stabilizing effect of having wide spread cameras with large mutual baselines is exploited. Experimental results are presented for both finite and infinite reference planes. An especially interesting application of this method is the reconstruction of architectural scenes with the reference plane taken as the plane at infinity which is visible via three orthogonal vanishing points. This is demonstrated by reconstructing the outside and inside (courtyard) of a building on the basis of 35 views in one single SVD.
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