3D Metric Rectification using Angle Regularity

Aamer Zaheer, Sohaib Khan
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引用次数: 2

Abstract

This paper proposes Automatic Metric Rectification of projectively distorted 3D structures for man-made scenes using Angle Regularity. Man-made scenes, such as buildings, are characterized by a profusion of mutually orthogonal planes and lines. Assuming the availability of planar segmentation, we search for the rectifying 3D homography which maximizes the number of orthogonal plane-pairs in the structure. We formulate the orthogonality constraints in terms of the Absolute Dual Quadric (ADQ). Using RANSAC, we first estimate the ADQ which maximizes the number of planes meeting at right angles. A rectifying homography recovered from the ADQ is then used as an initial guess for nonlinear refinement. Quantitative experiments show that the method is highly robust to the amount of projective distortion, the number of outliers (i.e. non-orthogonal planes) and noise in structure recovery. Unlike previous literature, this method does not rely on any knowledge of the cameras or images, and no global model, such as Manhattan World, is imposed.
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使用角度规则的三维度量校正
提出了一种基于角度规则的人工场景投影变形三维结构自动度量校正方法。人造场景,如建筑物,其特点是大量相互正交的平面和线条。假设平面分割的可用性,我们搜索使结构中正交平面对数量最大化的校正三维单应性。我们用绝对对偶二次函数(ADQ)来表述正交性约束。使用RANSAC,我们首先估计了最大平面直角相遇数量的ADQ。从ADQ中恢复的整流单应式然后用作非线性细化的初始猜测。定量实验表明,该方法对结构恢复中的投影失真量、离群点(即非正交平面)数量和噪声具有较强的鲁棒性。与以往的文献不同,这种方法不依赖于相机或图像的任何知识,也没有强加全球模型,如曼哈顿世界。
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