Detection and typification of linear structures for dynamic visualization of 3D city models
Detection and typification of linear structures for dynamic visualization of 3D city models
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DOI：
10.1016/j.compenvurbsys.2011.10.001
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发表时间：
2012-05
期刊：
影响因子：
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通讯作者：
Bo Mao;L. Harrie;Y. Ban
中科院分区：
文献类型：
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作者：
Bo Mao;L. Harrie;Y. Ban
杂波是三维城市模型可视化中的一个基本问题。本文提出了一种通过对线性建筑群进行类型化来消除杂波的新方法。该方法既适用于三维城市模型的静态可视化，也适用于动态可视化。该方法首先将具有更高详图级别(LOD)的建筑模型转换为具有地面平面和高度的LoD1。然后根据建筑物平面图之间的距离生成最小生成树。在最小二乘法的基础上，对线性建筑群进行检测以进行类型化。建筑群的类型化程度取决于它到视点的距离以及它的视角。接下来，将删除选定的建筑，并在每个组中分别调整其余建筑。为了保持建筑特征及其空间分布，使用属性关系图(ARG)和嵌套推土机距离(NEMD)来评价原始建筑对象与广义建筑对象之间的差异。实验结果表明，该方法在减少建筑物数量的同时，保持了城市区域的视觉相似性。
Cluttering is a fundamental problem in 3D city model visualization. In this paper, a novel method for removing cluttering by typification of linear building groups is proposed. This method works in static as well as dynamic visualization of 3D city models. The method starts by converting building models in higher Levels of Details (LoDs) into LoD1 with ground plan and height. Then the Minimum Spanning Tree (MST) is generated according to the distance between the building ground plans. Based on the MST, linear building groups are detected for typification. The typification level of a building group is determined by its distance to the viewpoint as well as its viewing angle. Next, the selected buildings are removed and the remaining ones are adjusted in each group separately. To preserve the building features and their spatial distribution, Attributed Relational Graph (ARG) and Nested Earth Mover’s Distance (NEMD) are used to evaluate the difference between the original building objects and the generalized ones. The experimental results indicate that our method can reduce the number of buildings while preserving the visual similarity of the urban areas.