Using stroke and mesh to recognize building group patterns
Using stroke and mesh to recognize building group patterns
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DOI：
10.1080/23729333.2019.1574371
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发表时间：
2019-04
影响因子：
0.5
通讯作者：
Xiao Wang;D. Burghardt
中科院分区：
文献类型：
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作者：
Xiao Wang;D. Burghardt
摘要 建筑图案是重要的结构，应该在地图概括中保留。然而，虽然建筑数据集中没有明确描述建筑模式，但地图读者可以轻松感知建筑模式。因此，为了更好地支持地图泛化，自动识别此类数据集中的建筑模式非常重要。本文首先提出了不同建筑模式的扩展和集成类型学。根据类型学，使用笔画和网格来识别建筑图案。该方法首先构建建筑物的邻近图，然后引入六个约束（距离、大小、形状、方向、伸长率和朝向比）来细化原始邻近图。笔划和网格源自精炼的邻近图，分别用于识别线性和网格构建模式。所提出的方法在代表不同模式类型的四个区域中进行了测试。专家调查评估识别结果，并与最小生成树方法进行比较。评估表明，郊区和农村地区的线性和网格模式得到了令人满意的结果。
ABSTRACT Building patterns are crucial structures and should be preserved in map generalization. However, while building patterns are not explicitly described in building datasets, map readers perceive building patterns effortlessly. Hence, to better support map generalization, it is important to automatically recognize building patterns in such datasets. This paper first proposes an extended and integrated typology of different building patterns. Based on the typology, building patterns are recognized using stroke and mesh. This method first structures the proximity graph of buildings, and then introduces six constraints (distance, size, shape, orientation, elongation, and facing ratio) to refine the original proximity graph. Strokes and meshes are derived from the refined proximity graph, and are used to recognize linear and grid building patterns, respectively. The proposed method is tested in four regions that are representative of different pattern types. The recognition results are evaluated in an expert survey and compared with the minimum spanning tree method. Assessment suggests that the linear and grid patterns in suburban and rural areas are recognized with satisfying results.