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Segmentation of Wooden Members of Ancient Architecture from Range Image

机译:从距离图像分割古代建筑的木制构件。

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摘要

Segmentation wooden member from range images is the basis of 3d reconstruction of wooden member and whole architecture because it provides reliable point clouds for modeling. This paper presents a segmentation strategy to extract point clouds of wooden member of ancient architecture from range image. Hybrid approach combining edge and region-based techniques is adopted in the paper to ensure a reliable and robust segmentation. First, range image is triangulated according to the implied topological relationships between point clouds. Second, filtering is processed by combination the two smoothing methods of λ∣μ and Laplacian. Third, feature points are detected by local surface differential geometry properties, and feature edges are extracted according to a selective mechanism, so an initial, rough segmentation is provided based on edge information. And then, the initial edge-based segmentation is enhanced by region-based segmentation method. How to estimate the differential geometry properties robustly, and how to detect feature points and feature edges and so on are studied in the paper. Range images acquired from Forbidden City of China are used to test the segmentation strategy, and results prove its efficiency and robustness.
机译:从距离图像中分割木制构件是木制构件和整个建筑的3d重建的基础,因为它为建模提供了可靠的点云。本文提出了一种从距离图像中提取古建筑木构件点云的分割策略。本文采用结合了基于边缘和区域技术的混合方法,以确保可靠且鲁棒的分割。首先,根据点云之间隐含的拓扑关系对距离图像进行三角剖分。其次,通过结合λ∣μ和拉普拉斯算子的两种平滑方法来处理滤波。第三,通过局部表面微分几何特性检测特征点,并根据选择机制提取特征边缘,因此基于边缘信息提供了初始的粗略分割。然后,通过基于区域的分割方法增强了基于边缘的初始分割。本文研究了如何鲁棒地估计微分几何特性,以及如何检测特征点和特征边缘等。从中国紫禁城获得的距离图像用于测试分割策略,结果证明了其有效性和鲁棒性。

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