多视图重复结构检测

Nianjuan Jiang, P. Tan, L. Cheong
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引用次数: 23

摘要

对称,尤其是建筑中的重复结构,在不同的国家和文化中普遍存在。现有的检测方法主要集中在从单幅图像中检测平面图案。建筑中有大量的非平面的三维重复元素(如阳台、窗户)和曲面,因此很难应用它们来检测重复结构。我们研究了这种建筑的多幅图像的重复结构检测问题。我们的方法联合分析这些图像和一组由它们重建的三维点通过运动结构算法。三维点有助于纠正几何变形并假设可能的晶格结构,而图像提供更密集的颜色和纹理信息来评估和确认这些假设。在实验中,我们将该方法与现有算法进行了比较。我们还展示了如何使用我们的结果来辅助基于图像的建模。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-view repetitive structure detection
Symmetry, especially repetitive structures in architecture are universally demonstrated across countries and cultures. Existing detection methods mainly focus on the detection of planar patterns from a single image. It is difficult to apply them to detect repetitive structures in architecture, which abounds with non-planar 3D repetitive elements (such as balconies and windows) and curved surfaces. We study the repetitive structure detection problem from multiple images of such architecture. Our method jointly analyzes these images and a set of 3D points reconstructed from them by structure-from-motion algorithms. 3D points help to rectify geometric deformations and hypothesize possible lattice structures, while images provide denser color and texture information to evaluate and confirm these hypotheses. In the experiments, we compare our method with existing algorithm. We also show how our results might be used to assist image-based modeling.
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