基于视觉认知理论的三维建筑群模型分层聚类概括方法
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摘要
针对三维建筑群模型简化难题,该文提出一种基于视觉认知理论的模型群组聚类概括方法。该方法利用道路要素对场景进行粗划分;然后利用方向、面积、高度等空间认知要素及其拓扑关系约束进行精分类,使其符合城市形态学特征;采用Delaunay三角网和边界追踪综合算法进行模型合并概括,并对模型进行分层存储。应用典型城市建筑群模型进行验证,结果表明:该算法简化效率高,分类结果符合人的认知习惯,并且通过聚类概括过程中各阈值的自适应控制,对于不同的模型,概括层次能够达到相对统一。
Aiming at the problem of simplification of 3D building group model,this paper proposes a generalized clustering method based on visual cognition theory.The method uses road elements to make rough classification of the scene,and then uses spatial cognitive elements such as direction,area and height to classify the scene and make it conform to the morphological characteristics of the city.Delaunay triangulation network and boundary tracking algorithm are used to model merging,and the models are stored in different layers.The algorithm is verified by the application of typical urban building group model.The experimental results show that the algorithm proposed in this paper has high efficiency,the classification results conform to people′s cognitive habits;by the self-adaption of all thresholds in the process of clustering generalization,the generalization levels of different models can be relatively unified.
Aiming at the problem of simplification of 3D building group model,this paper proposes a generalized clustering method based on visual cognition theory.The method uses road elements to make rough classification of the scene,and then uses spatial cognitive elements such as direction,area and height to classify the scene and make it conform to the morphological characteristics of the city.Delaunay triangulation network and boundary tracking algorithm are used to model merging,and the models are stored in different layers.The algorithm is verified by the application of typical urban building group model.The experimental results show that the algorithm proposed in this paper has high efficiency,the classification results conform to people′s cognitive habits;by the self-adaption of all thresholds in the process of clustering generalization,the generalization levels of different models can be relatively unified.
引文
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[2]YANG L,ZHANG L,MA J,et al.Interactive visualization of multi-resolution urban building models considering spatial cognition[J].International Journal of Geographical Information Science,2011,25(1):5-24.
[3]ZHANG L,DENG H,CHEN D,et al.A spatial cognition based urban building clustering approach and its applications[J].International Journal of Geographical Information Science,2012,27(4):721-740.
[4]KADA M.Aggregation of 3Dbuildings using a hybrid data approach[J].Cartography and Geographic Information Science,2011,38(2):153-160.
[5]刘文凯,唐建波,蔡建南,等.面向城市交通应用的移动对象聚类算法比较研究[J].地理与地理信息科学,2016,32(6):69-74.
[6]REGNAULD N.Contextual building typification in automated map generalization[J].Algorithmica,2001,30(2):312-333.
[7]GLANDER T,DOLLNER J.Abstract representations for interactive visualization of virtual 3Dcity models[J].Computers,Environment and Urban Systems,2009,33(5):375-387.
[8]ZHAO J,ZHU Q,DU Z,et al.Mathematical morphology based generalization of complex 3Dbuilding models incorporating semantic relationships[J].ISPRS Journal of Photogrammetry and Remote Sensing,2012,68:95-111.
[9]LYNCH K.The Image of the City[M].Cambridge,MA:MIT Press,1960.
[10]CHANG R,WESSEL G,KOSARA R,et al.Legible cities:Focus dependent multiple-resolution visualization of urban relationships[J].IEEE Transactions on Visualization and Computer Graphics,2007,13(6):1169-1175.
[11]潘文斌,刘坡,周洁萍,等.基于房屋轮廓与纹理的三维建筑模型分层次聚类研究[J].地球信息科学,2016,18(3):406-415.
[12]YAN H,WEIBEL R,YANG B.A multi-parameter approach to automated building grouping and generalization[J].GeoInformatica,2008,12(1):73-89.
[13]MAO B,BAN Y,HARRIE L.A multiple representation data structure for dynamic visualisation of generalised 3Dcity models[J].ISPRS Journal of Photogrammetry and Remote Sensing,2011,66(2):198-208.
[14]ALLOUCHE M K,MOULIN B.Amalgamation in cartographic generalization using Kohonen′s feature nets[J].International Journal of Geographical Information Science,2005,19(8-9):899-914.
[15]李德仁,赵中元,赵萍.城市规划三维决策支持系统设计与实现[J].武汉大学学报(信息科学版),2011,5(5):505-509.
[16]GLANDER T,DOLLNER J.Automated cell based generalization of virtual 3Dcity models with dynamic landmark highlighting[A].Proceedings of the 11th ICA Workshop on Generalization and Multiple Representation[C].2008.
[17]ZHANG M,ZHANG L,MATHIOPOULOS P T,et al.A geometry and texture coupled flexible generalization of urban building models[J].ISPRS Journal of Photogrammetry and Remote Sensing,2012,70(6):1-14.
[18]JIANG S,YANG B,SUN X.Multiple resolution representation of 3Dcomplex building models with features preservation[A].Proceedings of the 2011 19th International Conference on Geoinformatics[C].2011.
[19]LI Z,YAN H,AI T,et al.Automated building generalization based on urban morphology and Gestalt theory[J].International Journal of Geographical Information Science,2004,18(5):513-534.
[20]GUERCKE R,GTZELMANN T,BRENNER C,et al.Aggregation of LoD 1building models as an optimization problem[J].ISPRS Journal of Photogrammetry and Remote Sensing,2011,66(2):209-222.