基于重复结构检测的三维建筑物精细模型重建
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国家自然科学基金(61272309,61303138)


Repetition Detection Based 3D Reconstruction of Detailed Architectures
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National Natural Science Foundation of China (61272309, 61303138)

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    摘要:

    基于单幅图像的城市建筑物建模是计算机图形学和计算机视觉的一个研究热点.针对具有显著重复结构特征的单幅城市建筑物输入图像,提出了一种通过简单交互方便、快速地生成建筑物三维模型中精细细节结构的方法.首先,根据用户的简单交互重建建筑物基本主体部分的三维几何模型;然后,根据输入图像,通过检测水平方向和垂直方向上的边界线自动检测建筑物各个墙面的重复结构,并对重复细节结构按照其包围盒的特征进行分类;其次,通过用户描绘细节结构的局部线画图,根据建筑物细节结构与基本主体部分的射影几何关系,恢复对应凹凸细节结构的几何模型;最后,根据检测得到的建筑物表面重复结构,分别自动生成相同类型的重复细节结构,得到三维建筑物精细模型.实验结果表明,该方法能够简单、便捷地重建出具有较强真实感的三维建筑物模型.

    Abstract:

    In the literature of computer graphics and computer vision, single-image based 3D architecture modeling is a hot research topic. Focusing on repetition detection of urban architecture images, a novel algorithm for reconstructing detailed 3D architectures is presented for interactively generating large number of repetitive structures in an effective and convenient manner. The new approach consists of three steps. First, according to the parallel or vertical relations of sketch lines interactively drawn by the user, the coarse architectural model is reconstructed using an energy function optimization. Upon the texture information of the single input image, the horizontal and vertical repetitions on each architectural face are then detected and classified based on their bounding boxes. Next, according to the user inputted sketch lines of typical detailed structure, the 3D information of detailed concave or convex structures is calculated based on the projective relations between detailed structures and basic body of architecture. Finally, the other same type of repetitive structures are reconstructed automatically and their 3D detailed architectures can be generated. Experimental results show that the proposed method can conveniently and effectively reconstruct 3D detailed architectures from single image with high visual quality.

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缪永伟,冯小红,于莉洁,陈佳舟,李永水.基于重复结构检测的三维建筑物精细模型重建.软件学报,2016,27(10):2557-2573

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  • 收稿日期:2016-01-05
  • 最后修改日期:2016-03-29
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  • 在线发布日期: 2016-08-11
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