Template Matching and Simplification Method for Building Features Based on Shape Cognition
Template Matching and Simplification Method for Building Features Based on Shape Cognition
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基于形状认知的建筑特征模板匹配与简化方法
DOI：
10.3390/ijgi6080250
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发表时间：
2017-08
影响因子：
3.4
通讯作者：
Zhang Xiang
中科院分区：
文献类型：
--
作者：
Yan Xiongfeng;Ai Tinghua;Zhang Xiang
本研究基于建筑物分布和表征的典型模板特征，从形状认知的角度提出了一种模板匹配简化方法。该方法首先制定一系列模板，通过概括其多边形并分析其符号含义来抽象建筑物形状，然后通过搜索和匹配最相似的模板进行简化，以便以后可以用来替换原始建筑物。该方法在满足较小尺度下个体几何精度的前提下，能够增强对知名地标的印象，并通过符号模板反映测绘区域的格局。采用通过测量切线角随弧长变化来描述形状的转动函数来获得建筑物与模板多边形之间的相似距离，并使用最小二乘模型来控制候选模板的几何匹配。在真实数据集上进行实验以评估该方法的有用性，并将其与两种现有方法进行比较。实验表明，我们的方法可以保留建筑物形状的主要结构和几何精度。
This study proposes a template matching simplification method from the perspective of shape cognition based on the typical template characteristics of building distributions and representations. The method first formulates a series of templates to abstract the building shape by generalizing their polygons and analyzing their symbolic meanings, then conducts the simplification by searching and matching the most similar template that can be used later to replace the original building. On the premise of satisfying the individual geometric accuracy on a smaller scale, the proposed method can enhance the impression of well-known landmarks and reflect the pattern in mapping areas by the symbolic template. The turning function that describes shape by measuring the changes of the tangent-angle as a function of the arc-length is employed to obtain the similar distance between buildings and template polygons, and the least squares model is used to control the geometry matching of the candidate template. Experiments on real datasets are carried out to assess the usefulness of this method and compare it with two existing methods. The experiments suggest that our method can preserve the main structure of building shapes and geometric accuracy.
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影响因子：
1.4
作者：
A. MacEachren
通讯作者：
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DOI：
10.1080/13658810410001702021
发表时间：
2004-07-01
影响因子：
5.7
作者：
Li, Z;Yan, H;Chen, J
通讯作者：
Chen, J
DOI：
10.1080/13658810902798099
发表时间：
2010-02
影响因子：
5.7
作者：
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通讯作者：
Stefan Steiniger;P. Taillandier;R. Weibel
DOI：
10.5311/josis.2016.13.276
发表时间：
2016-12
期刊：
J. Spatial Inf. Sci.
影响因子：
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作者：
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通讯作者：
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DOI：
--
发表时间：
2007
期刊：
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影响因子：
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作者：
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Guo Ren-zhong