Decomposing Three Fundamental Matrices for Initializing 3-D Reconstruction from Three Views

Yasushi Kanazawa, Y. Sugaya, K. Kanatani
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引用次数: 2

Abstract

This paper focuses on initializing 3-D reconstruction from scratch without any prior scene information. Traditionally, this has been done from two-view matching, which is prone to the degeneracy called “imaginary focal lengths.” We overcome this difficulty by using three images, but we do not require three-view matching; all we need is three fundamental matrices separately computed from pair-wise image matching. We exploit the redundancy of the three fundamental matrices to optimize the camera parameters and the 3-D structure. The main theme of this paper is to give an analytical procedure for computing the positions and orientations of the three cameras and their internal parameters from three fundamental matrices. The emphasis is on resolving the ambiguity of the solution resulting from the sign indeterminacy of the fundamental matrices. We do numerical simulation to show that imaginary focal lengths are less likely for our three view methods, resulting in higher accuracy than the conventional two-view method. We also test the degeneracy tolerance capability of our method by using endoscopic intestine tract images, for which the camera configuration is almost always nearly degenerate. We demonstrate that our method allows us to obtain more detailed intestine structures than two-view reconstruction and observe how our three-view reconstruction is refined by bundle adjustment. Our method is expected to broaden medical applications of endoscopic images.
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分解三维重构初始化的三个基本矩阵
本文的重点是在没有任何先验场景信息的情况下,从头开始初始化三维重建。传统上,这是通过双视图匹配完成的,这很容易产生称为“虚焦距”的简并。我们通过使用三幅图像来克服这个困难,但我们不需要三视图匹配;我们所需要的是三个基本矩阵,分别从成对图像匹配中计算。我们利用三个基本矩阵的冗余来优化相机参数和三维结构。本文的主题是给出一种由三个基本矩阵计算三个相机的位置和方向及其内部参数的解析方法。重点是解决由基本矩阵的符号不确定性引起的解的模糊性。数值模拟结果表明,三种视点方法不太可能出现虚焦距,比传统的双视点方法具有更高的精度。我们还通过使用内镜下的肠道图像来测试我们的方法的退化耐受能力,其中相机配置几乎总是接近退化的。我们证明,我们的方法允许我们获得更详细的肠结构比二视图重建,并观察我们的三视图重建是如何细化束调整。我们的方法有望拓宽内窥镜图像的医学应用。
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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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