基于目标识别和参数化技术的城市建筑群三维重建研究
|
摘要
随着数字城市的快速发展和城市三维空间模型应用领域的不断扩展,城市建筑群三维模型的需求日益增长。然而传统建筑物三维重建方法在面对大空间尺度、大数据量、更新节奏快的城市建筑群时,在效率、精度、成本、尺度、技术门槛等方面均不同程度存在缺陷。为此,论文尝试引入目标识别和参数化技术,探求一种适用于城市建筑群的低成本、低门槛、高效率的“大众化”三维重建解决方案,以满足数字城市及相关领域的迫切需求。
论文的主要内容包括：(1)对建筑物三维重建、目标识别和参数化建模这三大领域的相关研究、技术方法作了总结回顾,指出了其存在的问题；(2)对三大技术体系作了深度解构,指出了“二元并行框架”的成因,给出了交叉的可行途径,并通过体系重构,构建了城市建筑群三维重建的“三元交叉框架”；(3)针对遥感影像分割,提出了面向对象的多尺度区域合并分割方法和基于量化合并代价的快速区域合并分割方法；(4)针对矢量图形优化,提出了基于删除代价的矢量图形单层次优化方法、面向遥感影像矢量化图形的多层次优化方法和面向建筑群的矩形拟合优化方法；(5)针对三维信息提取,提出了基于扩展统计模型的建筑群高度提取方法和三种城市建筑群层数估算模型,针对侧向航拍影像提出了一种建筑群坐标修正方法；(6)提出了“参-建分离”的系统架构。针对该架构中的参数管理模块,设计了参数的关联、组织、管理和属性块的恢复、管理等方法。针对服务网站模块,设计了风格库管理和项目库管理子模块。针对自动建模模块,提出了DXF-SHP文件格式自动转换,CGA文法规则和规则库框架设计,规则库的调用和参数值传递,以及自动化建模脚本的设计等系列方法；(7)集成关键技术方法,开发了城市建筑群三维重建软件原型系统(3DRS)及其子系统CBRS、CityUp,并以杭州市西湖区为案例开展了实证研究,从精度、效率、成本、技术门槛、时效性等方面验证了整套解决方案的可行性。
研究表明：(1)建筑物目标识别与参数化建模技术,恰可解决建筑物三维重建面临的两大难点；“三元交叉框架”使三大技术体系成为一个紧密连接、流程清晰、分工明确、目标一致的统一整体,为相关研究提供了理论支撑和方法指导；(2)面向对象的多尺度区域合并分割方法使综合考虑多种地物特征和多尺度分割成为可能,最大限度地缩短了队列长度,提高了分割精度和速度；基于量化合并代价的快速区域合并分割方法不仅能够保证分割精度,而且合并速度优势随初始分割区域数量的增加而越加显著；(3)相较于经典DP方法,基于删除代价的矢量图形单层次优化方法具有更高的精度和更低的时间复杂度,而且单位节点处理能力和等压缩率下的处理速度均具有显著优势；相较于传统单层次优化方法,面向遥感影像矢量化图形的多层次优化方法对影像不同的分割尺度和空间分辨率具有更强的适应性,能更好地还原地物的多层次特性；面向建筑群的矩形拟合优化方法可以有效减少最小面积外接矩形的计算时间,确保矩形对边平行、邻边垂直的关系,所得优化结果的形态和面积精度均较为理想；(4)基于扩展统计模型的建筑群高度提取方法、建筑群层数估算模型和建筑群坐标修正方法分别达到了较高的精度水平,可满足相关应用需求；(5)“参-建分离”的系统架构以及针对三大模块提出的一系列创新方法大幅降低了参数化建模平台的技术门槛和边际成本,提高了建模效率,为参数化技术的快速、广泛普及提供了新的发展思路；(6)本研究所提方法及系统在精度、效率、成本、门槛、时效性等方面均满足实验预定目标,体现了广泛的优势和大众化特性,整套解决方案具有可行性；(7)研究成果将推动数字城市三维空间数据基础设施的建设,使之在城市规划与管理、建筑景观设计、国防军事、应急救灾、环境保护、虚拟旅游、交通导航等诸多领域得到更广泛的应用。
With the rapid development of digital city and the constant expansion of city3D space model application fields, demand in the3D model of city buildings grows day by day. Nevertheless, facing city buildings with large spatial scale, huge data volume and quick data update demand, traditional buildings3D reconstruction method has some disadvantage in terms of efficiency, precision, cost, scale, technical threshold, etc. Hence, this essay attempted to introduce target recognition and parameterization technology, and presented a popular3D reconstruction solution with low cost, low threshold and high efficiency that adapt to city buildings, thus met the urgent demand for digital cities and related fields.
The main content of this essay is as follows. First, it summarized and reviewed three main fields including building3D reconstruction, target recognition and parametric modeling, and pointed out the existing problems of the above fields. Second, three major technology systems were deconstructed in depth and causes of "dual parallel framework" were pointed out as well. It also offered a practical way of the cross."Ternary cross framework" of3D reconstruction in city buildings was constructed through system reconfiguration. Third, aiming at remote sensing image segmentation, it also presents an object oriented multi-scale region merging method and a fast region merging method based on the classified merging cost. Fourth, aiming at vector graphics optimization, it presented a single-level optimization method for vector graphics based on deleting cost, a multi-level optimization method for remote sensing image vector graphics as well as a rectangle fitting optimization method for the building groups. Fifth, aiming at3D information extraction, it presents building height extraction method based on extended statistical model and three models to retrieve building storey information. A geometry correction method for building footprints aiming at lateral satellite images was also put forward. Sixth, a "parameter-modeling separation" system framework was presented. Aiming at parameter management module of this framework, the method of parameter association, organization and management as well as recovery and management of attribute block of CAD were designed. Composed of style library management and project library management sub-module, web site service module was designed. Aiming at automatic modeling module, DXF-SHP conversion, the design of the CGA syntax rules, rule library frame, rule library calling and parameter transmission as well as automatic modeling script were put forward. Seventh, through integrating key technology and methods, it also developed city buildings3D reconstruction software prototype system (3DRS) as well as its subsystem CBRS and CityUp. Meanwhile, empirical research was developed based on the example of the West Lake district in Hangzhou city. Also, the feasibility of the whole solutions was evaluated from the following aspects like precision, efficiency, cost, technical threshold, data presentalism, etc.
Research showed that, first, building target recognition and parametric modeling technology could exactly solve two difficult points of building3D reconstruction."Ternary cross framework" made three technology systems form a closely connected, procedure clear, division identified and target consistent unit, which offers theory support and method guidance for relevant research. Second, object oriented multi-scale region merging method made multi-scale segmentation in consideration of terrain features possible. By reducing the queue length to a large extent, segmentation precision and implementation speed was improved. Not only does the fast region merging method based on classified merging cost guarantee segmentation precision but also merging speed advantage becomes notable with the increase of the initial segmented region number. Third, compared with classical DP method, the single-level optimization method for vector graphics based on deleting cost was of higher precision and lower time complexity. Also, it outperformed the former in terms of processing capability per unit node and processing speed at the same compression ratio. Compared with the traditional single-level optimization method, multi-level optimization method for remote sensing image vector graphics had stronger adaptability to image segmentation scale and spatial resolution, which can better restore multilevel character of ground feature. Rectangle fitting optimization method for building groups could effectively reduce computation time of the minimum area bounding rectangle, ensured rectangles be parallel on opposite side and be perpendicular on adjacent side. The shape and area precision of the optimization result were both relatively ideal. Fourth, three methods including the building height extraction method based on extended statistical model, the building storey information retrieval method and the building footprint geometry correction method, respectively reached higher precision level and could meet corresponding application demand. Fifth, the "parameter-modeling separation" system framework and the series of innovation methods aiming at the three modules largely reduced technical threshold and marginal cost of parametric modeling platform and increased modeling efficiency, thus offering a brand-new strategy for the quick and widespread popularity of parameter technology. Sixth, methods and system proposed in this essay met the experiment's preseted target in terms of precision, efficiency, cost, threshold, data presentalism, etc. It showed comprehensive advantages with public orientation. The whole solutions are feasible. Seventh, it is very likely the research results will push forward the construction of3D digital city spatial data infrastructure, making it more widely used in urban planning and management, architecture and landscape design, national defense and military, emergency relief, environmental protection, virtual tourism, transportation navigation, etc.
论文的主要内容包括：(1)对建筑物三维重建、目标识别和参数化建模这三大领域的相关研究、技术方法作了总结回顾,指出了其存在的问题；(2)对三大技术体系作了深度解构,指出了“二元并行框架”的成因,给出了交叉的可行途径,并通过体系重构,构建了城市建筑群三维重建的“三元交叉框架”；(3)针对遥感影像分割,提出了面向对象的多尺度区域合并分割方法和基于量化合并代价的快速区域合并分割方法；(4)针对矢量图形优化,提出了基于删除代价的矢量图形单层次优化方法、面向遥感影像矢量化图形的多层次优化方法和面向建筑群的矩形拟合优化方法；(5)针对三维信息提取,提出了基于扩展统计模型的建筑群高度提取方法和三种城市建筑群层数估算模型,针对侧向航拍影像提出了一种建筑群坐标修正方法；(6)提出了“参-建分离”的系统架构。针对该架构中的参数管理模块,设计了参数的关联、组织、管理和属性块的恢复、管理等方法。针对服务网站模块,设计了风格库管理和项目库管理子模块。针对自动建模模块,提出了DXF-SHP文件格式自动转换,CGA文法规则和规则库框架设计,规则库的调用和参数值传递,以及自动化建模脚本的设计等系列方法；(7)集成关键技术方法,开发了城市建筑群三维重建软件原型系统(3DRS)及其子系统CBRS、CityUp,并以杭州市西湖区为案例开展了实证研究,从精度、效率、成本、技术门槛、时效性等方面验证了整套解决方案的可行性。
研究表明：(1)建筑物目标识别与参数化建模技术,恰可解决建筑物三维重建面临的两大难点；“三元交叉框架”使三大技术体系成为一个紧密连接、流程清晰、分工明确、目标一致的统一整体,为相关研究提供了理论支撑和方法指导；(2)面向对象的多尺度区域合并分割方法使综合考虑多种地物特征和多尺度分割成为可能,最大限度地缩短了队列长度,提高了分割精度和速度；基于量化合并代价的快速区域合并分割方法不仅能够保证分割精度,而且合并速度优势随初始分割区域数量的增加而越加显著；(3)相较于经典DP方法,基于删除代价的矢量图形单层次优化方法具有更高的精度和更低的时间复杂度,而且单位节点处理能力和等压缩率下的处理速度均具有显著优势；相较于传统单层次优化方法,面向遥感影像矢量化图形的多层次优化方法对影像不同的分割尺度和空间分辨率具有更强的适应性,能更好地还原地物的多层次特性；面向建筑群的矩形拟合优化方法可以有效减少最小面积外接矩形的计算时间,确保矩形对边平行、邻边垂直的关系,所得优化结果的形态和面积精度均较为理想；(4)基于扩展统计模型的建筑群高度提取方法、建筑群层数估算模型和建筑群坐标修正方法分别达到了较高的精度水平,可满足相关应用需求；(5)“参-建分离”的系统架构以及针对三大模块提出的一系列创新方法大幅降低了参数化建模平台的技术门槛和边际成本,提高了建模效率,为参数化技术的快速、广泛普及提供了新的发展思路；(6)本研究所提方法及系统在精度、效率、成本、门槛、时效性等方面均满足实验预定目标,体现了广泛的优势和大众化特性,整套解决方案具有可行性；(7)研究成果将推动数字城市三维空间数据基础设施的建设,使之在城市规划与管理、建筑景观设计、国防军事、应急救灾、环境保护、虚拟旅游、交通导航等诸多领域得到更广泛的应用。
With the rapid development of digital city and the constant expansion of city3D space model application fields, demand in the3D model of city buildings grows day by day. Nevertheless, facing city buildings with large spatial scale, huge data volume and quick data update demand, traditional buildings3D reconstruction method has some disadvantage in terms of efficiency, precision, cost, scale, technical threshold, etc. Hence, this essay attempted to introduce target recognition and parameterization technology, and presented a popular3D reconstruction solution with low cost, low threshold and high efficiency that adapt to city buildings, thus met the urgent demand for digital cities and related fields.
The main content of this essay is as follows. First, it summarized and reviewed three main fields including building3D reconstruction, target recognition and parametric modeling, and pointed out the existing problems of the above fields. Second, three major technology systems were deconstructed in depth and causes of "dual parallel framework" were pointed out as well. It also offered a practical way of the cross."Ternary cross framework" of3D reconstruction in city buildings was constructed through system reconfiguration. Third, aiming at remote sensing image segmentation, it also presents an object oriented multi-scale region merging method and a fast region merging method based on the classified merging cost. Fourth, aiming at vector graphics optimization, it presented a single-level optimization method for vector graphics based on deleting cost, a multi-level optimization method for remote sensing image vector graphics as well as a rectangle fitting optimization method for the building groups. Fifth, aiming at3D information extraction, it presents building height extraction method based on extended statistical model and three models to retrieve building storey information. A geometry correction method for building footprints aiming at lateral satellite images was also put forward. Sixth, a "parameter-modeling separation" system framework was presented. Aiming at parameter management module of this framework, the method of parameter association, organization and management as well as recovery and management of attribute block of CAD were designed. Composed of style library management and project library management sub-module, web site service module was designed. Aiming at automatic modeling module, DXF-SHP conversion, the design of the CGA syntax rules, rule library frame, rule library calling and parameter transmission as well as automatic modeling script were put forward. Seventh, through integrating key technology and methods, it also developed city buildings3D reconstruction software prototype system (3DRS) as well as its subsystem CBRS and CityUp. Meanwhile, empirical research was developed based on the example of the West Lake district in Hangzhou city. Also, the feasibility of the whole solutions was evaluated from the following aspects like precision, efficiency, cost, technical threshold, data presentalism, etc.
Research showed that, first, building target recognition and parametric modeling technology could exactly solve two difficult points of building3D reconstruction."Ternary cross framework" made three technology systems form a closely connected, procedure clear, division identified and target consistent unit, which offers theory support and method guidance for relevant research. Second, object oriented multi-scale region merging method made multi-scale segmentation in consideration of terrain features possible. By reducing the queue length to a large extent, segmentation precision and implementation speed was improved. Not only does the fast region merging method based on classified merging cost guarantee segmentation precision but also merging speed advantage becomes notable with the increase of the initial segmented region number. Third, compared with classical DP method, the single-level optimization method for vector graphics based on deleting cost was of higher precision and lower time complexity. Also, it outperformed the former in terms of processing capability per unit node and processing speed at the same compression ratio. Compared with the traditional single-level optimization method, multi-level optimization method for remote sensing image vector graphics had stronger adaptability to image segmentation scale and spatial resolution, which can better restore multilevel character of ground feature. Rectangle fitting optimization method for building groups could effectively reduce computation time of the minimum area bounding rectangle, ensured rectangles be parallel on opposite side and be perpendicular on adjacent side. The shape and area precision of the optimization result were both relatively ideal. Fourth, three methods including the building height extraction method based on extended statistical model, the building storey information retrieval method and the building footprint geometry correction method, respectively reached higher precision level and could meet corresponding application demand. Fifth, the "parameter-modeling separation" system framework and the series of innovation methods aiming at the three modules largely reduced technical threshold and marginal cost of parametric modeling platform and increased modeling efficiency, thus offering a brand-new strategy for the quick and widespread popularity of parameter technology. Sixth, methods and system proposed in this essay met the experiment's preseted target in terms of precision, efficiency, cost, threshold, data presentalism, etc. It showed comprehensive advantages with public orientation. The whole solutions are feasible. Seventh, it is very likely the research results will push forward the construction of3D digital city spatial data infrastructure, making it more widely used in urban planning and management, architecture and landscape design, national defense and military, emergency relief, environmental protection, virtual tourism, transportation navigation, etc.
引文
[1]Abraham L, Sasikumar M. Automatic Building Extraction from Satellite Images using Artificial Neural Networks[J]. Procedia Engineering,2012,50:893-903.
[2]Adams R, Bischof L. Seeded region growing[J]. IEEE Trans. Pattern Analysis and Machine Intelligence,1994,16:641-647.
[3]Ah-Soon C, Tombre K. Architectural symbol recognition using a network of constraints[J]. Pattern Recognition Letters,2001,22(2):231-248.
[4]Baatz M, Schape A. Multiresolution Segmentation:an optimization approach for high quality multi-scale image segmentation[C]:Angewandte Geographische Informationsverarbeitung XII, Wichmann-Verlag,2000. Heidelberg.
[5]Bakolas R. Virtual Urbanity:A parametric tool for the generation of virtual cities[D]. master degree thesis, London:University of London,2007.
[6]Black N D, Millar R J, Kunt M, et al. Second-generation image coding[M]:Elsevier, 2000:1-54.
[7]Blaschke T, Lang S, Lorup E, et al. Object-Oriented Image Processing in an Integrated GIS/Remote Sensing Environment and Perspectives for Environmental Applications[J]. Environmental Information for Planning,2000(2):555-570.
[8]Briese C. Structure line modeling based on terrestrial laserscanner data[C]:ISPRS Symposium, Dresden,2006.
[9]Cao G, Yang X, Mao Z. A Two-Stage Level Set Evolution Scheme for Man-Made Objects Detection in Aerial Images[C]:IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), NW Washington,2005. IEEE Computer Society.
[10]Cardenas C A, University H. Modeling strategies:Parametric design for fabrication in architectural practice[M]:Harvard University,2007.
[11]Carron T, Lambert P. Color edge detector using jointly hue, saturation and intensityf J]. IEEE International Conference on Image Processing,1994:977-1081.
[12]Castleman K. R数字图像处理[M].朱志刚等,译.北京：电子工业出版社,2002.
[13]Chen G, Esch G, Wonka P, et al. Interactive procedural street modeling[C]:SIGGRAPH '08, New York, NY, USA,2008. ACM.
[14]Cheng F, Thiel K H. Delimiting the building heights in a city from the shadow in panchromatic SPOT-Image-Part 1-Test of Forty Two Buildings[J]. International Journal of Remote Sensing,1995,16(3):409-415.
[15]Cheng H D, Jiang X H, Sun Y, et al. Color image segmentation[J]. Pattern Recognition, 2001,34(12):2259-2281.
[16]Coyne B, Sproat R. WordsEye:An Automatic Text-to-Scene Conversion System[C]: Proceeding of Computer Graphics, ACM SIGGRAPH, Los Angles,2001.
[17]Day M. The trouble with BIM[EB/OL]. http://aecmag.com/index.php?option=com_content&task=view&id=450.
[18]De Halleux J. A C++implementation of Douglas-Peucker line approximation algorithm[EB/OL]. http://www.codeproject.com/KB/recipes/dphull.aspx.
[19]Definiens. eCognition Developer 8 User Guide(version 1.2.0)[M]. Germany:Definiens AG,2009.
[20]Dosch P, Tombre K, Ah-Soon C, et al. A complete system for the analysis of architectural drawings[J]. International Journal on Document Analysis and Recognition,2000,2(3): 102-116.
[21]Douglas D H, Peucker T K. Algorithms for the reduction of the number of points required to represent a digitized line or its caricature[J]. Cartographica:The International Journal for Geographic Information and Geovisualization,1973,10(2):112-122.
[22]Doxygen. Gdal Class Hierarchy[EB/OL]. http://www.gdal.org/ogr/hierarchy.html.
[23]Duarte J P, Rocha J, Ducla-Soares G, et al. An urban grammar for the Medina of Marrakech[C]:The 2nd International Conference on Design Computing and Cognition, Netherlands,2006. Springer.
[24]Dylla K, Frischer B, Mueller P, et al. Rome Reborn 2.0:A Case Study of Virtual City Reconstruction Using Procedural Modeling Techniques[C]:CAA 2009. Proceedings of the 37th Annual Computer Applications and Quantitative Methods in Archaeology Conference, Williamsburg, Virginia, USA,2010. ArchaeoPress.
[25]Ebisch K. A correction to the Douglas-Peucker line generalization algorithm[J]. Computers & Geosciences,2002,28(8):995-997.
[26]Erlandsson F, Linnman C, Ekholm S, et al. A Detailed Analysis of Cyclin A Accumulation at the G1/S Border in Normal and Transformed Cells[J]. Experimental Cell Research,2000, 259(1):86-95.
[27]Esri. CityEngine Help[EB/OL]. http://www.esri.com.
[28]Fabris A E, Forrest A R. Antialiasing of Curves by Discrete Pre-filtering[C]:SIGGRAPH '97, New York, NY, USA,1997. ACM Press/Addison-Wesley Publishing Co.
[29]Finkelstein A. lecture notes[M/OL].2003. http://www.cs.princeton.edu/courses/archive/spr03/cs426/lectures/16-procedural.pdf.
[30]Gerke M, Heipke C, Straub B. Building extraction from aerial imagery using a generic scene model and invariant geometric moments[C]:IEEE/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas, Rome,2001.
[31]Ghali, Sherif. Constructive Solid Geometry[M]:Springer London,2008:277-283.
[32]Ghassan K, Veronique G, Rene C. Controlling object natural behaviors in a 3D declarative modeler[C]:Proceeding of Computer Graphics International, Hanover, Germany,1998.
[33]Glass K. R, Orkel C, Bangay S D. Duplicating Road Patterns in South African Informal Settlements Using Procedural Techniques[C]:Proceedings of the 4th International Conference on Computer Graphics,2006.
[34]Gruen A, Nevatia R. Automatic Building Extraction from Aerial Images[J]. Computer Vision and Image Understanding,1998,73(2):1-2.
[35]Gruen A, Xinhua W. Creation of A 3D City Model of Zurich With CC-Modeler[C]: Spatial Information Science,1998.
[36]Grun A, Dan H. TOBAGO-a topology builder for the automated generation of building models[M]. Automatic Extraction of Man-Made Objects from Aerial and Space Images II, Berlin:Birkhauser Verlag,1997:149-160.
[37]Hadid Z. One North Masterplan[EB/OL]. http://www.zaha-hadid.com/masterplans/one-north-masterplan/.
[38]Haris K, Efstratiadis S N, Maglaveras N, et al. Hybrid image segmentation using watersheds and fast region merging [J]. Image Processing, IEEE Transactions on,1998, 7(12):1684-1699.
[39]Hershberger J, Snoeyink J. Speeding Up the Douglas-Peucker Line-Simplification Algorithm[C]:The 5th International Symposium on Spatial Data Handling,1992.
[40]Hofmann A D. Analysis of Tin-structure parameter spaces in airborne laser scanner data for 3D building model generation[C]:International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Beijing,2004.
[41]Horna S, Damiand G, Meneveaux D, et al. Building 3D indoor scenes topology from 2D architectural plans[C]:Computer Graphics Theory and Applications. GRAPP'2007, Barcelona, Spain,2007.
[42]Hueckel M H. An operator which locates edges in digitized pictures[J]. J. Assoc. Comput. Mach.,1971,18(1):113-125.
[43]Inglada J, Giros A. Automatic man-made object recognition in high resolution remote sensing images[C]:IGARSS04,2004.
[44]Irvin R B, Mckeown D M. Methods for exploiting the relationship between buildings and their shadows in aerial imagery[J].1989.19(6):1564-1575.
[45]Jinghui D, Veronique P, Hanqing L. Building extraction in urban areas from satellite images using GIS data as prior information[C]:IGARSS04,2004.
[46]Karantzalos K, Paragios N. Recognition-driven two-dimensional competing priors toward automatic and accurate building detection[J]. IEEE Trans on Geoscience and Remote Sensing,2009,47(1):133-144.
[47]Lafarge F, Descombers X, Zerubia J, et al. Automatic building extraction from DEMs using an object approach and application to the 3D-city modeling[J]. Isprs Journal of Photogrammetry and Remote Sensing,2008,63(3):365-381.
[48]Lechner T, Ren P, Watson B, et al. Procedural Modeling of Urban Land Use[C]: Proceeding of Computer Graphics, ACM SIGGRAPH, Boston,2006.
[49]Lechner T, Watson B, Ren P, et al. Procedural Modeling of Land Use in Cities[M/OL]. Illinois Institute of Technology.2004.
[50]Lechner T, Watson B, Wilensky U, et al. Procedural city modeling[C]:1st Midwestern Graphics conference,2003.
[51]Legakis J, Dorsey J, Gortler S J. Feature-based Cellular Texturing for Architectural Models[C]:Proceeding of Computer Graphics, ACM SIGGRAPH,2001.
[52]LingBo新加坡One North总体规划[EB/OL]. http://www.ikuku.cn/7973.
[53]Littmann E, Ritter H. Adaptive color segmentation -- a comparison of neural and statistical methods[J]. IEEE Trans. Neural Network,1997,8(1):175-185.
[54]Lu T, Tai C, Yang H. A novel knowledge-based system for interpreting complex engineering drawings:theory, representation, and implementation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2009,31(8):1444-1457.
[55]Lu Y, Behar E, Donnelly S, et al. Fast and robust generation of city-scale seamless 3D urban models[J]. Computer-Aided Design,2011,43(11):1380-1390.
[56]Maas H. Closed solutions for the determination of parametric building models from invariant moments of airborne laserscanner data[J]. International Archives of Photogrammetry and Remote Sensing,1999,32(3):193-199.
[57]Mayunga S D, Coleman D J, Zhang Y. A semi-automated approach for extracting buildings from QuickBird imagery applied to informal settlement mapping[J]. International Journal of Remote Sensing.2007,28(10):2343-2357.
[58]Muller P, Vereenooghe T, Wonka P, et al. Procedural 3D Reconstruction of Puuc Buildings in Xkipche[C]:The 7th International Symposium on Virtual Reality, Archaeology and Intelligent Cultural Heritage, Nicosia, Cyprus.2006. Eurographics Association.
[59]Muller P, Wonka P, Haegler S, et al. Procedural modeling of buildings[J]. ACM Trans. Graph.,2006,25:614-623.
[60]Miiller P, Zeng G, Wonka P, et al. Image-based procedural modeling of facades[J]. ACM Trans. Graph.,2007,26.
[61]Nagao M, Matsuyama T. A structural analysis of complex aerial photographs[M]. New York:Plenum,1980:199.
[62]Nagy D. Towards a Parametric Planning[EB/OL]. http://danilnagy.dreamstudionyc.com/index.php?/writing/towards-a-parametric-planning/.
[63]Noronha S, Nevatia R. Detection and Modeling of Buildings from Multiple Aerial Images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2001,23: 501-518.
[64]Parish Y I H, Muller P. Procedural modeling of cities[C]:SIGGRAPH'01, New York, NY, USA,2001. ACM.
[65]Park S M, Elnimeiri M, Sharpe D C, et al. Tall Building Form Generation by Parametric Design Process[C]:CTBUH 2004 Seoul Conference,2004. Illinois Institute of Technology.
[66]Pompidou,美国最普通住宅的建造过程[EB/OL]. http://bbs.tianya.cn/post-house-199585-1.shtml.
[67]Porway J, Wang K, Zhu S C. A hierarchical and contextual model for aerial image understanding[J]. International Journal Of Computer Vision,2010,88(2):254-283.
[68]Preiss B R. Data structures and algorithms with object-oriented design patterns in C++[M]. New York, USA:John Wiley & Sons, Inc,1999.
[69]Rotenberg S. Procedural Modeling[M/OL].2004. http://pisa.ucsd.edu/cse125/2004/lectures/procedural.pef.
[70]Rottensteiner F, Briese C. Automatic Generation of Building Models from Lidar Data and the Integration of Aerial Images[C]:International Society of Photogrammetry and Remote Sensing, Beijing,2003.
[71]Rottensteiner F, Trinder J, Clode S, et al. Building detection by fusion of airborne laser scanner data and multi-spectral images:Performance evaluation and sensitivity analysis[J]. ISPRS Journal of Photogrammetry and Remote Sensing,2007,62(2):135-149.
[72]Rout S, Srivastava S P, Majumdar J. Multi modal Image Segmentation Using a Modified Hopfield Neural Network[J]. Pattern Recognition,1998,31(6):743-750.
[73]Sahin C, Alkis A, Ergun B, et al. Producing 3D city model with the combined photogrammetric and laser scanner data in the example of Taksim Cumhuriyet square[J]. Optics and Lasers in Engineering,2012,50(12):1844-1853.
[74]Sandor B T, Metcalf D, Young-Jo K. Segmentation of brain CT image using the concept of region growing[J]. International Journal of Bio-Medical Computing,1991,29(2): 133-147.
[75]Sarfraz M, Khan M A. An automatic algorithm for approximating boundary of bitmap characters [J]. Future Generation Computer SystemsComputer Graphics and Geometric Modeling,2004,20(8):1327-1336.
[76]Schnabel M A, Karakiewicz J. Rethinking Parameters in Urban Design[J]. International Journal of Architectural Computing,2007,5(1):84-98.
[77]Schumacher P. The Parametricist Epoch:Let the Style Wars Begin[J]. The Architects' Journal,2010,231(16).
[78]Scut Wangxun参数化建模[EB/OL]. http://baike.baidu.com/view/4692993.htm.
[79]Shibasaki R, Takuma A, Zhao H, et al. A mobile user interface for 3D spatial database based on the fusion of live landscape imagery[C]:Proc. UM3'98,1998.
[80]Silva R C, Amorim L M E. Parametric urbanism:emergence, limits and perspectives of a new trend in urban design based on parametric design systems[J]. VIRUS,2010(3).
[81]Smelik R M, De Kraker K J, Groenewegen S A, et al. A Survey of Procedural Methods for Terrain Modelling[C],2009.
[82]Sohn G, Dowman I. Data fusion of high-resolution satellite imagery and LiDAR data for automatic building extraction[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2007,62(1):43-63.
[83]Song Z, Pan C, Yang Q. A Region-Based Approach to Building Detection in Densely Build-Up High Resolution Satellite Image[C]:IEEE International Conference On Image Processing, Atlanta, GA,2006.
[84]Stoney W E. ASPRS GUIDE TO LAND IMAGING SATELLITES[EB/OL]. http://www.asprs.org/Satellite-Information/Guides-to-Land-Imaging-Satellites-Historic.ht ml.
[85]Sun J, Baciu G, Yu X B, et al. Image-Based Template Generation of Road Networks for Virtual Maps[J]. International Journal of Image and Graphics,2004,4(4):701-720.
[86]Sun J, Yu X B, Baciu G, et al. Template-based generation of road networks for virtual city modeling[C]:Proceedings of the ACM symposium on virtual reality software and technology,2002.
[87]Suveg I, Vosselman G. Automatic 3D building reconstruction[C]:The International Society for Optical Engineering,2002.
[88]Takase Y, Sho N, Sone A, et al. Automatic Generation of 3D City Models and Related Applications[C]:Remote Sensing and Spatial Information Sciences(ISPRS), Tarasp, Switzerland,2003.
[89]Tang M, Anderson J. Information Urbanism:Parametric urbanism injunction with GIS data processing & fabrication[C]:2011 Annual Architectural Research Centers Consortium (ARCC) Spring Research Conference,2011.
[90]Tavakoli M, Rosenfeld A. Edge segment linking based on gray level and geometrical compatibilities[J]. Pattern Recognition,1982,15(5):369-377.
[91]Tong L, Yang H, Yang R, et al. Automatic analysis and integration of architectural drawings[J]. International Journal of Document Analysis and Recognition (IJDAR),2007, 9(1):31-47.
[92]Tournaire O, Bredif M, Boldo D, et al. An efficient stochastic approach for building footprint extraction from digital elevation models [J]. ISPRS Journal of Photogrammetry and Remote Sensing,2010,65(4):317-327.
[93]Tremeau A, Borel N. A region growing and merging algorithm to color segmentation[J]. Pattern Recognition,1997,30(7):1191-1203.
[94]Van den Heuvel F A. Reconstruction from a single architectural image from the Meydenbauer archives[C]:International Symposium of CIPA 2001, Potsdam,2001.
[95]Vilarino D L, Brea V M, Cabello D. Discrete time CNN for image segmentation by active contours[J]. Pattern Recognition Letters,1998,19(8):721-734.
[96]Vosselman G, Dijkman S.3D Building Model Reconstruction from Point Clouds and Ground PlansfC]:International Archives of Photogrammetry and Remote Sensing, Beijing, 2001.
[97]Walter E, Pronzato L. Identification of parametric models from experimental data[M]: Springer,1997.
[98]Wang Y, Adali T, Kung S Y. Quantification and segmentation of brain tissues from MR images a probabilistic neural network approach[J]. IEEE Transactions on image processing, 1998,7(8).
[99]Watson B, Muller P, Wonka P, et al. Urban Design and Procedural Modeling[C]: Proceeding of Computer Graphics, ACM SIGGRAPH, San Diego,2007.
[100]Watson B, Muller P, Wonka P, et al. Procedural Urban Modeling in Practice[J]. Computer Graphics and Applications, IEEE,2008,28(3):18-26.
[101]Weber B, Muller P, Wonka P, et al. Interactive Geometric S imulation of 4D Cities[C]: Eurographics 2009, Munich, Germany,2009. The Eurographics Association and Blackwell Publishing 2009.
[102]Wei Y, Zhao Z, Song J. Urban building extraction from high-resolution satellite panchromatic image using clustering and edge detection[C]:IGARSS04,2004.
[103]Wonka P, Hanson E, Mulier P, et al. Procedural modeling of urban environments[C]: Proceeding of Computer Graphics, ACM SIGGRAPH, Boston,2006.
[104]Wonka P, Wimmer M, Sillion F C C O, et al. Instant Architecture[J]. ACM Transactions on Graphics,2003,22(4):669-677.
[105]Wu S T, Marquez M R G. A non-self-intersection Douglas-Peucker algorithm[C]: Computer Graphics and Image Processing,2003. SIBGRAPI 2003. XVI Symposium on, Brazilian,2003.
[106]Wu X. Adaptive split-and-merge segmentation based on piecewise least-square approximation[J]. Pattern Analysis and Machine Intelligence, IEEE Transactions on,1993, 15(8):808-815.
[107]Yenerim D, Yan W. BIM-Based Parametric Modeling:A Case Study[C]:MSV'l1-The 2011 International Conference on Modeling, Simulation and Visualization Methods, Las Vegas, NV,2011.
[108]Yu H S. Parametric Architecture:Performative/Responsive assembly components[D]. master of science in architecture studies degree thesis, Cambridge:Massachusetts Institute of Technology,2009.
[109]Zhang K, Yan J, Chen S. Automatic Construction of Building Footprints From Airborne LIDAR Data[J]. IEEE Transactions on Geoscience and Remote Sensing,2006,44(9): 2523-2533.
[110]曹健.图像目标的表示与识别[M].北京：机械工业出版社,2012：204.
[111]曾齐红.机载激光雷达点云数据处理与建筑物三维重建[D].博士学位论文：上海大学,2009.
[112]柴树杉.DXF库(dxflib)使用指南[EB/OL]. http://chaishushan.blog.163.com/blog/static/130192897200911551858160/.
[113]常歌,黄野.基于CSG构件分析的建筑物模型提取方法[J].武汉测绘科技大学学报,2000,25(6)：520-524.
[114]陈磊,赵书河.基于开源类库OGR的空间数据互操作研究[C]：规范与服务·2008高校GIS论坛,北京,2008.
[115]陈秋晓.高分辨率遥感影像分割方法研究[D].博士学位论文,北京：中国科学院,2004.
[116]陈秋晓,陈述彭,周成虎.基于局域同质性梯度的遥感图像分割方法及其评价[J].遥感学报,2006,10(3)：357-365.
[117]陈仁喜,赵忠明,潘晶.遥感分类栅格图的快速矢量化方法[J].遥感学报,2006(3)：326-331.
[118]陈勇,黄波.矢量、栅格相互转换的新方法[J].遥感技术与应用,1995,10(3)：61-65.
[119]陈勇,唐敏,童若锋等.基于遗传模拟退火算法的不规则多边形排样[J].计算机辅助设计与图形学学报,2003,15(5)：598-609.
[120]丁宁,王倩,陈明九.基于三维激光扫描技术的古建保护分析与展望[J].山东建筑大学学报,2010,25(3)：274-276,284.
[121]董玉森,詹云军,杨树文.利用高分辨率遥感图像阴影信息提取建筑物高度[J].咸宁师专学报,2002,22(3)：93-96.
[122]段志彪,何耀帮.悬高测量法在检测建筑物高度中的应用[J].华北水利水电学院学报,2007,28(1)：40-42.
[123]付斌.基于活动轮廓模型的目标分割与跟踪的研究[D],哈尔滨：哈尔滨工业大学,2006.
[124]傅慧灵.地图数字化中矢量数据压缩算法研究[D].硕士学位论文：太原理工大学,2005.
[125]龚健雅.3维虚拟地球技术发展与应用[J].地理信息世界,2011,09(2)：15-17.
[126]郭平AutoCAD中的”属性块”及其应用[J].电子设计工程,2011,19(6)：30-32.
[127]何国金,陈刚,何晓云等.利用SPOT图象阴影提取城市建筑物高度及其分布信息[J].中国图象图形学报A辑,2001,6(5)：425-428.
[128]何涵晞.参数化城市设计——建筑信息模型在大规模城市设计的推广、案例与展望[EB/OL]. http://www.abbs.com.cn/at+d/2011/06/138-141.pdf.
[129]侯蕾,尹东,尤晓建.一种遥感图像中建筑物的自动提取方法[J].计算机仿真,2006,23(4)：184-187,224.
[130]胡春,张钧,田金文.城区三维景观重建中的建筑物提取[J].华中科技大学学报(自然科学版),2004,32(7)：43-45.
[131]胡长鹏,张巨俭,刘瑞璞.基于VLISP和OpenDCL的西装智能CAD系统的实现[J].天津工业大学学报,2010,29(5)：33-36.
[132]黄磊.基于图像序列的三维虚拟城市重建关键技术研究[D].硕士学位论文：中国海洋大学,2008.
[133]贾坤,李强子,田亦陈等.遥感影像分类方法研究进展[J].光谱学与光谱分析,2011,31(10)：2618-2623.
[134]兰度AutoCAD可视化对话框开发工具OpenDCL使用简介[J].城市勘测,2009(6)：87-89,92.
[135]雷友开,邱玉辉.基于自适应粒子群算法的约束布局优化研究[J].计算机研究与发展,2006,43(10)：1724-1731.
[136]李芳珍,许伦辉.DXF文件格式及其外部接口的研究[J].兵工自动化,2008,27(7)：83-85.
[137]李海月,王宏琦,陆见微等.遥感图像中建筑物自动识别与标绘方法研究[J].电子测量技术,2007,30(2)：15-20.
[138]李洪艳,曹建荣,谈文婷等.图像分割技术综述[J].山东建筑大学学报,2010,25(1)：85-89,93.
[139]李锦业,张磊,吴炳方等.基于高分辨率遥感影像的城市建筑密度和容积率提取方法研究[J].遥感技术与应用,2007,22(3)：309-313.
[140]李伟青.建筑构件智能识别方法研究[J].浙江大学学报(理学版),2005,32(4)：392-398.
[141]李占才,刘春燕.点阵图形矢量化的高效方法——有向边界法[J].计算机应用与软件,1997,14(3)：48-51.
[142]林辉.基于多特征的高分辨率遥感图像分类技术研究[D].博士学位论文：中南林学院中南林业科技大学,2005.
[143]林瑶,田捷.医学图像分割方法综述[J].模式识别与人工智能,2002,15(2)：192-204.
[144]刘传亮,陆建德AutoCAD DXF文件格式与二次开发图形软件编程[J].微机发展,2004,14(9)：101-104.
[145]刘春,李楠,吴杭彬等.机载激光扫描中复杂建筑物轮廓线平差提取模型[J].同济大学学报(自然科学版),2012,40(9)：1399-1405.
[146]刘锋,张继贤,李海涛.SHP文件格式的研究与应用[J].测绘科学,2006,31(6)：116-117.
[147]刘华,华炜,周栋等.语义规则驱动的中国古代建筑造型[J].计算机辅助设计与图形学学报,2004,16(10)：1335-1340.
[148]刘建聪.森林资源矢量数据边界优化算法研究与应用[D].硕士学位论文：中南林业科技大学,2011.
[149]刘可晶.一种改进的矢量曲线数据压缩算法[J].甘肃科学学报,2005,17(3)：112-115.
[150]刘龙飞,牟伶俐,王兴玲等.利用阴影计算建筑物高度的模型比较分析[J].世界科技研究与发展,2010,32(1)：39-42.
[151]刘露.全球海量遥感影像数据的分布式管理技术研究[D].硕士学位论文：国防科学技术大学,2007.
[152]龙文志.建筑业应尽快推行建筑信息模型(BIM)技术[J].建筑技术,2011,42(1)：9-14.
[153]陆丽珍,刘仁义,刘南.一种融合颜色和纹理特征的遥感图像检索方法[J].中国图象图形学报,2004,9(3)：328-333.
[154]陆再林,张树有,谭建荣等.基于工程特征类的预算工程量自适应提取方法研究[J].计算机辅助设计与图形学学报,2001,13(12)：1101-1105.
[155]骆剑承,周成虎,沈占锋等.遥感信息图谱计算的理论方法研究[J].地球信息科学学报,2009,11(5)：664-669.
[156]梅雪良.航空影像中规则房屋三维形体的自动重建[D].博士学位论文：武汉测绘科技大学武汉大学,1997.
[157]孟祥旭,徐延宁.参数化设计研究[J].计算机辅助设计与图形学学报,2002,14(11)：1086-1090.
[158]明冬萍,骆剑承,沈占锋等.高分辨率遥感影像信息提取与目标识别技术研究[J].测绘科学,2005,30(3)：18-20.
[159]冉琼,迟耀斌,王智勇等.基于“北京一号”小卫星影像阴影的建筑物高度测算研究[J].遥感信息,2008(4)：18-21.
[160]任自珍,岑敏仪,张同刚等LiDAR数据中建筑物提取的新方法-Fc-S法[J].测绘科学,2010,35(6)：134-136,141.
[161]阮秋琦.数字图像处理学[M],北京：电子工业出版社,2001：390.
[162]萨师炬,王珊.数据库系统概论[G],北京：高等教育出版社,2004.
[163]邵巨良.小波理论——影像分析与目标识别[M]：武汉测绘科技大学出版社,1993：162.
[164]邵振峰.基于航空立体影像对的人工目标三维提取与重建[D].博士学位论文：武汉大学,2004.
[165]沈蔚,李京,陈云浩等.基于LIDAR数据的建筑轮廓线提取及规则化算法研究[J].遥感学报,2008,12(5)：692-698.
[166]沈文.”参数化主义”的崛起——新建筑时代的到来[J].城市环境设计,2010(8)：194-199.
[167]沈掌泉,王人潮.基于拓扑关系原理的栅格转换矢量方法的研究[J].遥感学报,1999,3(1)：38-42.
[168]宋世军,石来德,乔彩凤.运动人体图像分割算法研究[J].中国工程机械学报,2007,7(5)：16-21.
[169]孙善芳.从航空影像提取城区表面信息[D].博士学位论文：武汉测绘科技大学武汉大学,1994.
[170]谭衢霖,王今飞.结合高分辨率多光谱影像和LiDAR数据提取城区建筑[J].应用基础与工程科学学报,2011,19(5)：741-748.
[171]唐亮.城市航空影像关键地物提取技术研究[D].博士学位论文：西安电子科技大学,2004.
[172]唐亮,谢维信,黄建军等.从航空影像中自动提取高层建筑物[J].计算机学报,2005,28(7)：1199-1204.
[173]陶闯.从大比例尺黑白航空影象提取地物信息----一种基于人机协同的目标导引技术[D].硕士学位论文：武汉测绘科技大学武汉大学,1993.
[174]陶金花,苏林,李树楷.一种从激光雷达点云中提取建筑物模型的方法[J].红外与激光工程,2009,38(2)：340-345.
[175]陶文兵,柳健,田金文.一种新型的航空图像城区建筑物自动提取方法[J].计算机学报,2003,26(7)：866-873.
[176]田新光,张继贤,张永红.利用QuickBird影像的阴影提取建筑物高度[J].测绘科学,2008,33(2)：88-89,77.
[177]宛延琦.工程数据库系统[G],北京：清华大学出版社,1999.
[178]万剑华.城市3维地理信息系统的建模研究[D],武汉：武汉大学,2001.
[179]王爱民,沈兰荪.图像分割研究综述[J].测控技术,2000,19(5)：1-7.
[180]王继周,李成名.城市景观三维模型库的原理、构建及应用[J].测绘科学,2007,32(4)：20-22.
[181]王家耀,宁津生,张祖勋.中国数字城市建设方案及推进战略研究[M].北京：科学出版社,2008.
[182]王健,靳奉祥,李云岭等.三维激光扫描技术在城市三维数字景观建模中的应用[c]：2008年测绘科学前沿技术论坛,南京,2008.
[183]王俊,朱利.基于图像匹配-点云融合的建筑物立面三维重建[J].计算机学报,2012,35(10)：2072-2079.
[184]王丽英.城市环境的过程式建模技术研究[D].博士学位论文：浙江大学计算机科学学院浙江大学,2009.
[185]王伟,黄雯雯,镇姣Pictometry倾斜摄影技术及其在3维城市建模中的应用[J].测绘与空间地理信息,2011,34(3)：181-183.
[186]王永会,王勇勇,王守金.基于TIN和CSG的三维城市建模方法[J].沈阳建筑大学学报(自然科学版),2012,28(3)：563-568.
[187]翁姝.区域建筑物三维重建技术与实现[D].硕士学位论文：华中师范大学,2011.
[188]吴慧欣,薛惠锋,邢书宝.限定TIN与CSG集成仿真模型生成算法研究[J].计算机应用,2007,27(2)：475-478.
[189]吴晶晶.“十二五”期间我国全部地级市将建成数字城市[EB/OL].http://www.gov.cn/jrzg/2012-09/10/content_2221342.htm.
[190]吴静,靳奉祥,王健.基于三维激光扫描数据的建筑物三维建模[J].测绘工程,2007, 16(5)：57-60.
[191]吴军.3维城市建模中的建筑墙面纹理快速重建研究[J].测绘学报,2005,34(4)：317-323.
[192]吴秦.STL之Map[EB/OL]. http://www.cnblogs.com/skynet/archive/2010/06/18/1760518.html.
[193]夏春林,王佳奇3DGIS中建筑物三维建模技术综述[J].测绘科学,2011,36(1)：70-72.
[194]谢军飞,李延明.利用IKONOS卫星图像阴影提取城市建筑物高度信息[J].国土资源遥感,2004(4)：4-6.
[195]谢顺平,都金康,王结臣.实现栅格图形和图像数据矢量化提取的游程轮廓追踪法[J].遥感学报,2004,8(5)：465-470.
[196]谢亦才,李岩Douglas-Peucker算法在无拓扑矢量数据压缩中的改进[J].计算机工程与应用,2009,45(32)：189-192.
[197]辛大永.建设工程竣工验收建筑高度测量几点问题的探讨[J].黑龙江科技信息,2010(6)：260.
[198]徐丰.参数化城市主义——一个理解城市的新的角度[J].城市建筑,2010(6)：47-50.
[199]徐丰,金亚秋.多方位高分辨率SAR的三维目标自动重建(二)多方位重建[J].电波科学学报,2008,23(1)：23-33.
[200]徐明霞.三维城市景观建模技术在小区规划中的应用[D].硕士学位论文：长安大学,2006.
[201]薛强,张志强,孙济渊.一种用于建筑物场景重建的方法[J].计算机工程,2004,30(6)：179-181.
[202]杨得志,王杰臣,闾国年.矢量数据压缩的Douglas-Peucker算法的实现与改进[J].测绘通报,2002(7)：18-19.
[203]杨建宇,杨崇俊,明冬萍等WebGIS系统中矢量数据的压缩与化简方法综述[J].计算机工程与应用,2004,40(32)：36-38,92.
[204]杨长江,陈冲.再论建筑物高度的测量方法[J].测绘通报,2005(8)：47-48.
[205]叶齐祥,高文,王伟强等.一种融合颜色和空间信息的彩色图像分割算法[J].软件学报,2004(4)：522-530.
[206]尹平,王润生.基于边缘信息的分开合并图像分割算法[J].中国图象图形学报,1998,3A(6)：450-454.
[207]尤红建.激光三维遥感数据处理及建筑物重建[M].北京：测绘出版社,2006.
[208]游亚鹏,杨剑雷.“参数化实现”设计的一个建筑实例杭州奥体中心体育游泳馆[J].城市环境设计,2012(4)：240-251.
[209]虞自奋.属性块在工程图形中的研究与应用[J].天津冶金,2008(3)：28-30.
[210]袁晓辉,金立左,李久贤等.基于兴趣区检测与分析的水上桥梁识别[J].红外与毫米波学报,2003,22(5)：331-336.
[211]张桂芳,单新建,尹京苑等.单幅高空间分辨率卫星图像提取建筑物三维信息的方法研究[J].地震地质,2007,29(1)：180-187.
[212]张昊LIDAR建筑物提取方法研究[D].硕士学位论文：中国民航大学,2007.
[213]张卡,盛业华,李永强等.基于数字近景立体摄影的三维表面模型构建[J].数据采集与处理,2007,22(3)：309-314.
[214]张鹏,李伟,胡诚轶.城市高层建筑物高度的检测方法之一——悬高测量法[J].科技信息(学术版),2008(12)：269-272.
[215]张平,王文伟,吴丽芸.基于均匀性图分水岭变换及两步区域合并的彩色图像分割[J].计算机应用,2006(6)：1378-1380.
[216]张莎莎.图像分割与运动目标跟踪算法研究[D],哈尔滨：哈尔滨工业大学,2006.
[217]张树有,彭群生,谭建荣.基于空间基坐标的尺寸可标注性判别研究[J].计算机学报,2000,23(9)：982-986.
[218]张颖,吴成东,原宝龙.机器人路径规划方法综述[J].控制工程,2003,10增刊：152-154.
[219]张煜,张祖勋,张剑清.几何约束与影像分割相结合的快速半自动房屋提取[J].武汉测绘科技大学学报,2000,25(3)：238-242.
[220]章孝灿,潘云鹤.GIS中基于“栅格技术”的栅格数据矢量化技术[J].计算机辅助设计与图形学学报,2001,13(10)：895-900.
[221]章毓晋.图像分割[M].北京：科学出版社,2001.
[222]赵斌.高层建筑施工GPS测量技术分析[J].科技资讯,2010(19)：93.
[223]赵锦艳.建筑图重建技术及其模型信息提取方法的研究[J].湖南工业大学学报,2009,23(4)：41-44.
[224]赵锦艳,刘任任,王兆其等.一种基于抽象语义识别的交互式三维建筑物重建系统[C]：第七届全国虚拟现实与可视化学术会议,北京,2007.
[225]赵俊娟,尹京苑,单新建.基于高分辨率卫星影像的建筑物轮廓矢量化技术[J].防灾减灾工程学报,2004,24(2)：153-157.
[226]周俊,晏非,孙曼.基于区域分割合并的建筑物半自动提取方法[J].海洋测绘,2005,25(1)：58-60.
[227]周亚男,沈占锋,骆剑承等.阴影辅助下的面向对象城市建筑物提取[J].地理与地理信息科学,2010,26(3)：37-40.
[228]朱国敏,马照亭,孙隆祥等.城市三维地理信息系统中三维模型的快速构建方法[J].地理与地理信息科学,2007,23(4)：29-32,40.
[229]左建章,关艳玲,朱强.大范围三维城市立体景观建模系统的研究[J].测绘科学,2005,30(2)：22-24.
[2]Adams R, Bischof L. Seeded region growing[J]. IEEE Trans. Pattern Analysis and Machine Intelligence,1994,16:641-647.
[3]Ah-Soon C, Tombre K. Architectural symbol recognition using a network of constraints[J]. Pattern Recognition Letters,2001,22(2):231-248.
[4]Baatz M, Schape A. Multiresolution Segmentation:an optimization approach for high quality multi-scale image segmentation[C]:Angewandte Geographische Informationsverarbeitung XII, Wichmann-Verlag,2000. Heidelberg.
[5]Bakolas R. Virtual Urbanity:A parametric tool for the generation of virtual cities[D]. master degree thesis, London:University of London,2007.
[6]Black N D, Millar R J, Kunt M, et al. Second-generation image coding[M]:Elsevier, 2000:1-54.
[7]Blaschke T, Lang S, Lorup E, et al. Object-Oriented Image Processing in an Integrated GIS/Remote Sensing Environment and Perspectives for Environmental Applications[J]. Environmental Information for Planning,2000(2):555-570.
[8]Briese C. Structure line modeling based on terrestrial laserscanner data[C]:ISPRS Symposium, Dresden,2006.
[9]Cao G, Yang X, Mao Z. A Two-Stage Level Set Evolution Scheme for Man-Made Objects Detection in Aerial Images[C]:IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), NW Washington,2005. IEEE Computer Society.
[10]Cardenas C A, University H. Modeling strategies:Parametric design for fabrication in architectural practice[M]:Harvard University,2007.
[11]Carron T, Lambert P. Color edge detector using jointly hue, saturation and intensityf J]. IEEE International Conference on Image Processing,1994:977-1081.
[12]Castleman K. R数字图像处理[M].朱志刚等,译.北京：电子工业出版社,2002.
[13]Chen G, Esch G, Wonka P, et al. Interactive procedural street modeling[C]:SIGGRAPH '08, New York, NY, USA,2008. ACM.
[14]Cheng F, Thiel K H. Delimiting the building heights in a city from the shadow in panchromatic SPOT-Image-Part 1-Test of Forty Two Buildings[J]. International Journal of Remote Sensing,1995,16(3):409-415.
[15]Cheng H D, Jiang X H, Sun Y, et al. Color image segmentation[J]. Pattern Recognition, 2001,34(12):2259-2281.
[16]Coyne B, Sproat R. WordsEye:An Automatic Text-to-Scene Conversion System[C]: Proceeding of Computer Graphics, ACM SIGGRAPH, Los Angles,2001.
[17]Day M. The trouble with BIM[EB/OL]. http://aecmag.com/index.php?option=com_content&task=view&id=450.
[18]De Halleux J. A C++implementation of Douglas-Peucker line approximation algorithm[EB/OL]. http://www.codeproject.com/KB/recipes/dphull.aspx.
[19]Definiens. eCognition Developer 8 User Guide(version 1.2.0)[M]. Germany:Definiens AG,2009.
[20]Dosch P, Tombre K, Ah-Soon C, et al. A complete system for the analysis of architectural drawings[J]. International Journal on Document Analysis and Recognition,2000,2(3): 102-116.
[21]Douglas D H, Peucker T K. Algorithms for the reduction of the number of points required to represent a digitized line or its caricature[J]. Cartographica:The International Journal for Geographic Information and Geovisualization,1973,10(2):112-122.
[22]Doxygen. Gdal Class Hierarchy[EB/OL]. http://www.gdal.org/ogr/hierarchy.html.
[23]Duarte J P, Rocha J, Ducla-Soares G, et al. An urban grammar for the Medina of Marrakech[C]:The 2nd International Conference on Design Computing and Cognition, Netherlands,2006. Springer.
[24]Dylla K, Frischer B, Mueller P, et al. Rome Reborn 2.0:A Case Study of Virtual City Reconstruction Using Procedural Modeling Techniques[C]:CAA 2009. Proceedings of the 37th Annual Computer Applications and Quantitative Methods in Archaeology Conference, Williamsburg, Virginia, USA,2010. ArchaeoPress.
[25]Ebisch K. A correction to the Douglas-Peucker line generalization algorithm[J]. Computers & Geosciences,2002,28(8):995-997.
[26]Erlandsson F, Linnman C, Ekholm S, et al. A Detailed Analysis of Cyclin A Accumulation at the G1/S Border in Normal and Transformed Cells[J]. Experimental Cell Research,2000, 259(1):86-95.
[27]Esri. CityEngine Help[EB/OL]. http://www.esri.com.
[28]Fabris A E, Forrest A R. Antialiasing of Curves by Discrete Pre-filtering[C]:SIGGRAPH '97, New York, NY, USA,1997. ACM Press/Addison-Wesley Publishing Co.
[29]Finkelstein A. lecture notes[M/OL].2003. http://www.cs.princeton.edu/courses/archive/spr03/cs426/lectures/16-procedural.pdf.
[30]Gerke M, Heipke C, Straub B. Building extraction from aerial imagery using a generic scene model and invariant geometric moments[C]:IEEE/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas, Rome,2001.
[31]Ghali, Sherif. Constructive Solid Geometry[M]:Springer London,2008:277-283.
[32]Ghassan K, Veronique G, Rene C. Controlling object natural behaviors in a 3D declarative modeler[C]:Proceeding of Computer Graphics International, Hanover, Germany,1998.
[33]Glass K. R, Orkel C, Bangay S D. Duplicating Road Patterns in South African Informal Settlements Using Procedural Techniques[C]:Proceedings of the 4th International Conference on Computer Graphics,2006.
[34]Gruen A, Nevatia R. Automatic Building Extraction from Aerial Images[J]. Computer Vision and Image Understanding,1998,73(2):1-2.
[35]Gruen A, Xinhua W. Creation of A 3D City Model of Zurich With CC-Modeler[C]: Spatial Information Science,1998.
[36]Grun A, Dan H. TOBAGO-a topology builder for the automated generation of building models[M]. Automatic Extraction of Man-Made Objects from Aerial and Space Images II, Berlin:Birkhauser Verlag,1997:149-160.
[37]Hadid Z. One North Masterplan[EB/OL]. http://www.zaha-hadid.com/masterplans/one-north-masterplan/.
[38]Haris K, Efstratiadis S N, Maglaveras N, et al. Hybrid image segmentation using watersheds and fast region merging [J]. Image Processing, IEEE Transactions on,1998, 7(12):1684-1699.
[39]Hershberger J, Snoeyink J. Speeding Up the Douglas-Peucker Line-Simplification Algorithm[C]:The 5th International Symposium on Spatial Data Handling,1992.
[40]Hofmann A D. Analysis of Tin-structure parameter spaces in airborne laser scanner data for 3D building model generation[C]:International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Beijing,2004.
[41]Horna S, Damiand G, Meneveaux D, et al. Building 3D indoor scenes topology from 2D architectural plans[C]:Computer Graphics Theory and Applications. GRAPP'2007, Barcelona, Spain,2007.
[42]Hueckel M H. An operator which locates edges in digitized pictures[J]. J. Assoc. Comput. Mach.,1971,18(1):113-125.
[43]Inglada J, Giros A. Automatic man-made object recognition in high resolution remote sensing images[C]:IGARSS04,2004.
[44]Irvin R B, Mckeown D M. Methods for exploiting the relationship between buildings and their shadows in aerial imagery[J].1989.19(6):1564-1575.
[45]Jinghui D, Veronique P, Hanqing L. Building extraction in urban areas from satellite images using GIS data as prior information[C]:IGARSS04,2004.
[46]Karantzalos K, Paragios N. Recognition-driven two-dimensional competing priors toward automatic and accurate building detection[J]. IEEE Trans on Geoscience and Remote Sensing,2009,47(1):133-144.
[47]Lafarge F, Descombers X, Zerubia J, et al. Automatic building extraction from DEMs using an object approach and application to the 3D-city modeling[J]. Isprs Journal of Photogrammetry and Remote Sensing,2008,63(3):365-381.
[48]Lechner T, Ren P, Watson B, et al. Procedural Modeling of Urban Land Use[C]: Proceeding of Computer Graphics, ACM SIGGRAPH, Boston,2006.
[49]Lechner T, Watson B, Ren P, et al. Procedural Modeling of Land Use in Cities[M/OL]. Illinois Institute of Technology.2004.
[50]Lechner T, Watson B, Wilensky U, et al. Procedural city modeling[C]:1st Midwestern Graphics conference,2003.
[51]Legakis J, Dorsey J, Gortler S J. Feature-based Cellular Texturing for Architectural Models[C]:Proceeding of Computer Graphics, ACM SIGGRAPH,2001.
[52]LingBo新加坡One North总体规划[EB/OL]. http://www.ikuku.cn/7973.
[53]Littmann E, Ritter H. Adaptive color segmentation -- a comparison of neural and statistical methods[J]. IEEE Trans. Neural Network,1997,8(1):175-185.
[54]Lu T, Tai C, Yang H. A novel knowledge-based system for interpreting complex engineering drawings:theory, representation, and implementation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2009,31(8):1444-1457.
[55]Lu Y, Behar E, Donnelly S, et al. Fast and robust generation of city-scale seamless 3D urban models[J]. Computer-Aided Design,2011,43(11):1380-1390.
[56]Maas H. Closed solutions for the determination of parametric building models from invariant moments of airborne laserscanner data[J]. International Archives of Photogrammetry and Remote Sensing,1999,32(3):193-199.
[57]Mayunga S D, Coleman D J, Zhang Y. A semi-automated approach for extracting buildings from QuickBird imagery applied to informal settlement mapping[J]. International Journal of Remote Sensing.2007,28(10):2343-2357.
[58]Muller P, Vereenooghe T, Wonka P, et al. Procedural 3D Reconstruction of Puuc Buildings in Xkipche[C]:The 7th International Symposium on Virtual Reality, Archaeology and Intelligent Cultural Heritage, Nicosia, Cyprus.2006. Eurographics Association.
[59]Muller P, Wonka P, Haegler S, et al. Procedural modeling of buildings[J]. ACM Trans. Graph.,2006,25:614-623.
[60]Miiller P, Zeng G, Wonka P, et al. Image-based procedural modeling of facades[J]. ACM Trans. Graph.,2007,26.
[61]Nagao M, Matsuyama T. A structural analysis of complex aerial photographs[M]. New York:Plenum,1980:199.
[62]Nagy D. Towards a Parametric Planning[EB/OL]. http://danilnagy.dreamstudionyc.com/index.php?/writing/towards-a-parametric-planning/.
[63]Noronha S, Nevatia R. Detection and Modeling of Buildings from Multiple Aerial Images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2001,23: 501-518.
[64]Parish Y I H, Muller P. Procedural modeling of cities[C]:SIGGRAPH'01, New York, NY, USA,2001. ACM.
[65]Park S M, Elnimeiri M, Sharpe D C, et al. Tall Building Form Generation by Parametric Design Process[C]:CTBUH 2004 Seoul Conference,2004. Illinois Institute of Technology.
[66]Pompidou,美国最普通住宅的建造过程[EB/OL]. http://bbs.tianya.cn/post-house-199585-1.shtml.
[67]Porway J, Wang K, Zhu S C. A hierarchical and contextual model for aerial image understanding[J]. International Journal Of Computer Vision,2010,88(2):254-283.
[68]Preiss B R. Data structures and algorithms with object-oriented design patterns in C++[M]. New York, USA:John Wiley & Sons, Inc,1999.
[69]Rotenberg S. Procedural Modeling[M/OL].2004. http://pisa.ucsd.edu/cse125/2004/lectures/procedural.pef.
[70]Rottensteiner F, Briese C. Automatic Generation of Building Models from Lidar Data and the Integration of Aerial Images[C]:International Society of Photogrammetry and Remote Sensing, Beijing,2003.
[71]Rottensteiner F, Trinder J, Clode S, et al. Building detection by fusion of airborne laser scanner data and multi-spectral images:Performance evaluation and sensitivity analysis[J]. ISPRS Journal of Photogrammetry and Remote Sensing,2007,62(2):135-149.
[72]Rout S, Srivastava S P, Majumdar J. Multi modal Image Segmentation Using a Modified Hopfield Neural Network[J]. Pattern Recognition,1998,31(6):743-750.
[73]Sahin C, Alkis A, Ergun B, et al. Producing 3D city model with the combined photogrammetric and laser scanner data in the example of Taksim Cumhuriyet square[J]. Optics and Lasers in Engineering,2012,50(12):1844-1853.
[74]Sandor B T, Metcalf D, Young-Jo K. Segmentation of brain CT image using the concept of region growing[J]. International Journal of Bio-Medical Computing,1991,29(2): 133-147.
[75]Sarfraz M, Khan M A. An automatic algorithm for approximating boundary of bitmap characters [J]. Future Generation Computer SystemsComputer Graphics and Geometric Modeling,2004,20(8):1327-1336.
[76]Schnabel M A, Karakiewicz J. Rethinking Parameters in Urban Design[J]. International Journal of Architectural Computing,2007,5(1):84-98.
[77]Schumacher P. The Parametricist Epoch:Let the Style Wars Begin[J]. The Architects' Journal,2010,231(16).
[78]Scut Wangxun参数化建模[EB/OL]. http://baike.baidu.com/view/4692993.htm.
[79]Shibasaki R, Takuma A, Zhao H, et al. A mobile user interface for 3D spatial database based on the fusion of live landscape imagery[C]:Proc. UM3'98,1998.
[80]Silva R C, Amorim L M E. Parametric urbanism:emergence, limits and perspectives of a new trend in urban design based on parametric design systems[J]. VIRUS,2010(3).
[81]Smelik R M, De Kraker K J, Groenewegen S A, et al. A Survey of Procedural Methods for Terrain Modelling[C],2009.
[82]Sohn G, Dowman I. Data fusion of high-resolution satellite imagery and LiDAR data for automatic building extraction[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2007,62(1):43-63.
[83]Song Z, Pan C, Yang Q. A Region-Based Approach to Building Detection in Densely Build-Up High Resolution Satellite Image[C]:IEEE International Conference On Image Processing, Atlanta, GA,2006.
[84]Stoney W E. ASPRS GUIDE TO LAND IMAGING SATELLITES[EB/OL]. http://www.asprs.org/Satellite-Information/Guides-to-Land-Imaging-Satellites-Historic.ht ml.
[85]Sun J, Baciu G, Yu X B, et al. Image-Based Template Generation of Road Networks for Virtual Maps[J]. International Journal of Image and Graphics,2004,4(4):701-720.
[86]Sun J, Yu X B, Baciu G, et al. Template-based generation of road networks for virtual city modeling[C]:Proceedings of the ACM symposium on virtual reality software and technology,2002.
[87]Suveg I, Vosselman G. Automatic 3D building reconstruction[C]:The International Society for Optical Engineering,2002.
[88]Takase Y, Sho N, Sone A, et al. Automatic Generation of 3D City Models and Related Applications[C]:Remote Sensing and Spatial Information Sciences(ISPRS), Tarasp, Switzerland,2003.
[89]Tang M, Anderson J. Information Urbanism:Parametric urbanism injunction with GIS data processing & fabrication[C]:2011 Annual Architectural Research Centers Consortium (ARCC) Spring Research Conference,2011.
[90]Tavakoli M, Rosenfeld A. Edge segment linking based on gray level and geometrical compatibilities[J]. Pattern Recognition,1982,15(5):369-377.
[91]Tong L, Yang H, Yang R, et al. Automatic analysis and integration of architectural drawings[J]. International Journal of Document Analysis and Recognition (IJDAR),2007, 9(1):31-47.
[92]Tournaire O, Bredif M, Boldo D, et al. An efficient stochastic approach for building footprint extraction from digital elevation models [J]. ISPRS Journal of Photogrammetry and Remote Sensing,2010,65(4):317-327.
[93]Tremeau A, Borel N. A region growing and merging algorithm to color segmentation[J]. Pattern Recognition,1997,30(7):1191-1203.
[94]Van den Heuvel F A. Reconstruction from a single architectural image from the Meydenbauer archives[C]:International Symposium of CIPA 2001, Potsdam,2001.
[95]Vilarino D L, Brea V M, Cabello D. Discrete time CNN for image segmentation by active contours[J]. Pattern Recognition Letters,1998,19(8):721-734.
[96]Vosselman G, Dijkman S.3D Building Model Reconstruction from Point Clouds and Ground PlansfC]:International Archives of Photogrammetry and Remote Sensing, Beijing, 2001.
[97]Walter E, Pronzato L. Identification of parametric models from experimental data[M]: Springer,1997.
[98]Wang Y, Adali T, Kung S Y. Quantification and segmentation of brain tissues from MR images a probabilistic neural network approach[J]. IEEE Transactions on image processing, 1998,7(8).
[99]Watson B, Muller P, Wonka P, et al. Urban Design and Procedural Modeling[C]: Proceeding of Computer Graphics, ACM SIGGRAPH, San Diego,2007.
[100]Watson B, Muller P, Wonka P, et al. Procedural Urban Modeling in Practice[J]. Computer Graphics and Applications, IEEE,2008,28(3):18-26.
[101]Weber B, Muller P, Wonka P, et al. Interactive Geometric S imulation of 4D Cities[C]: Eurographics 2009, Munich, Germany,2009. The Eurographics Association and Blackwell Publishing 2009.
[102]Wei Y, Zhao Z, Song J. Urban building extraction from high-resolution satellite panchromatic image using clustering and edge detection[C]:IGARSS04,2004.
[103]Wonka P, Hanson E, Mulier P, et al. Procedural modeling of urban environments[C]: Proceeding of Computer Graphics, ACM SIGGRAPH, Boston,2006.
[104]Wonka P, Wimmer M, Sillion F C C O, et al. Instant Architecture[J]. ACM Transactions on Graphics,2003,22(4):669-677.
[105]Wu S T, Marquez M R G. A non-self-intersection Douglas-Peucker algorithm[C]: Computer Graphics and Image Processing,2003. SIBGRAPI 2003. XVI Symposium on, Brazilian,2003.
[106]Wu X. Adaptive split-and-merge segmentation based on piecewise least-square approximation[J]. Pattern Analysis and Machine Intelligence, IEEE Transactions on,1993, 15(8):808-815.
[107]Yenerim D, Yan W. BIM-Based Parametric Modeling:A Case Study[C]:MSV'l1-The 2011 International Conference on Modeling, Simulation and Visualization Methods, Las Vegas, NV,2011.
[108]Yu H S. Parametric Architecture:Performative/Responsive assembly components[D]. master of science in architecture studies degree thesis, Cambridge:Massachusetts Institute of Technology,2009.
[109]Zhang K, Yan J, Chen S. Automatic Construction of Building Footprints From Airborne LIDAR Data[J]. IEEE Transactions on Geoscience and Remote Sensing,2006,44(9): 2523-2533.
[110]曹健.图像目标的表示与识别[M].北京：机械工业出版社,2012：204.
[111]曾齐红.机载激光雷达点云数据处理与建筑物三维重建[D].博士学位论文：上海大学,2009.
[112]柴树杉.DXF库(dxflib)使用指南[EB/OL]. http://chaishushan.blog.163.com/blog/static/130192897200911551858160/.
[113]常歌,黄野.基于CSG构件分析的建筑物模型提取方法[J].武汉测绘科技大学学报,2000,25(6)：520-524.
[114]陈磊,赵书河.基于开源类库OGR的空间数据互操作研究[C]：规范与服务·2008高校GIS论坛,北京,2008.
[115]陈秋晓.高分辨率遥感影像分割方法研究[D].博士学位论文,北京：中国科学院,2004.
[116]陈秋晓,陈述彭,周成虎.基于局域同质性梯度的遥感图像分割方法及其评价[J].遥感学报,2006,10(3)：357-365.
[117]陈仁喜,赵忠明,潘晶.遥感分类栅格图的快速矢量化方法[J].遥感学报,2006(3)：326-331.
[118]陈勇,黄波.矢量、栅格相互转换的新方法[J].遥感技术与应用,1995,10(3)：61-65.
[119]陈勇,唐敏,童若锋等.基于遗传模拟退火算法的不规则多边形排样[J].计算机辅助设计与图形学学报,2003,15(5)：598-609.
[120]丁宁,王倩,陈明九.基于三维激光扫描技术的古建保护分析与展望[J].山东建筑大学学报,2010,25(3)：274-276,284.
[121]董玉森,詹云军,杨树文.利用高分辨率遥感图像阴影信息提取建筑物高度[J].咸宁师专学报,2002,22(3)：93-96.
[122]段志彪,何耀帮.悬高测量法在检测建筑物高度中的应用[J].华北水利水电学院学报,2007,28(1)：40-42.
[123]付斌.基于活动轮廓模型的目标分割与跟踪的研究[D],哈尔滨：哈尔滨工业大学,2006.
[124]傅慧灵.地图数字化中矢量数据压缩算法研究[D].硕士学位论文：太原理工大学,2005.
[125]龚健雅.3维虚拟地球技术发展与应用[J].地理信息世界,2011,09(2)：15-17.
[126]郭平AutoCAD中的”属性块”及其应用[J].电子设计工程,2011,19(6)：30-32.
[127]何国金,陈刚,何晓云等.利用SPOT图象阴影提取城市建筑物高度及其分布信息[J].中国图象图形学报A辑,2001,6(5)：425-428.
[128]何涵晞.参数化城市设计——建筑信息模型在大规模城市设计的推广、案例与展望[EB/OL]. http://www.abbs.com.cn/at+d/2011/06/138-141.pdf.
[129]侯蕾,尹东,尤晓建.一种遥感图像中建筑物的自动提取方法[J].计算机仿真,2006,23(4)：184-187,224.
[130]胡春,张钧,田金文.城区三维景观重建中的建筑物提取[J].华中科技大学学报(自然科学版),2004,32(7)：43-45.
[131]胡长鹏,张巨俭,刘瑞璞.基于VLISP和OpenDCL的西装智能CAD系统的实现[J].天津工业大学学报,2010,29(5)：33-36.
[132]黄磊.基于图像序列的三维虚拟城市重建关键技术研究[D].硕士学位论文：中国海洋大学,2008.
[133]贾坤,李强子,田亦陈等.遥感影像分类方法研究进展[J].光谱学与光谱分析,2011,31(10)：2618-2623.
[134]兰度AutoCAD可视化对话框开发工具OpenDCL使用简介[J].城市勘测,2009(6)：87-89,92.
[135]雷友开,邱玉辉.基于自适应粒子群算法的约束布局优化研究[J].计算机研究与发展,2006,43(10)：1724-1731.
[136]李芳珍,许伦辉.DXF文件格式及其外部接口的研究[J].兵工自动化,2008,27(7)：83-85.
[137]李海月,王宏琦,陆见微等.遥感图像中建筑物自动识别与标绘方法研究[J].电子测量技术,2007,30(2)：15-20.
[138]李洪艳,曹建荣,谈文婷等.图像分割技术综述[J].山东建筑大学学报,2010,25(1)：85-89,93.
[139]李锦业,张磊,吴炳方等.基于高分辨率遥感影像的城市建筑密度和容积率提取方法研究[J].遥感技术与应用,2007,22(3)：309-313.
[140]李伟青.建筑构件智能识别方法研究[J].浙江大学学报(理学版),2005,32(4)：392-398.
[141]李占才,刘春燕.点阵图形矢量化的高效方法——有向边界法[J].计算机应用与软件,1997,14(3)：48-51.
[142]林辉.基于多特征的高分辨率遥感图像分类技术研究[D].博士学位论文：中南林学院中南林业科技大学,2005.
[143]林瑶,田捷.医学图像分割方法综述[J].模式识别与人工智能,2002,15(2)：192-204.
[144]刘传亮,陆建德AutoCAD DXF文件格式与二次开发图形软件编程[J].微机发展,2004,14(9)：101-104.
[145]刘春,李楠,吴杭彬等.机载激光扫描中复杂建筑物轮廓线平差提取模型[J].同济大学学报(自然科学版),2012,40(9)：1399-1405.
[146]刘锋,张继贤,李海涛.SHP文件格式的研究与应用[J].测绘科学,2006,31(6)：116-117.
[147]刘华,华炜,周栋等.语义规则驱动的中国古代建筑造型[J].计算机辅助设计与图形学学报,2004,16(10)：1335-1340.
[148]刘建聪.森林资源矢量数据边界优化算法研究与应用[D].硕士学位论文：中南林业科技大学,2011.
[149]刘可晶.一种改进的矢量曲线数据压缩算法[J].甘肃科学学报,2005,17(3)：112-115.
[150]刘龙飞,牟伶俐,王兴玲等.利用阴影计算建筑物高度的模型比较分析[J].世界科技研究与发展,2010,32(1)：39-42.
[151]刘露.全球海量遥感影像数据的分布式管理技术研究[D].硕士学位论文：国防科学技术大学,2007.
[152]龙文志.建筑业应尽快推行建筑信息模型(BIM)技术[J].建筑技术,2011,42(1)：9-14.
[153]陆丽珍,刘仁义,刘南.一种融合颜色和纹理特征的遥感图像检索方法[J].中国图象图形学报,2004,9(3)：328-333.
[154]陆再林,张树有,谭建荣等.基于工程特征类的预算工程量自适应提取方法研究[J].计算机辅助设计与图形学学报,2001,13(12)：1101-1105.
[155]骆剑承,周成虎,沈占锋等.遥感信息图谱计算的理论方法研究[J].地球信息科学学报,2009,11(5)：664-669.
[156]梅雪良.航空影像中规则房屋三维形体的自动重建[D].博士学位论文：武汉测绘科技大学武汉大学,1997.
[157]孟祥旭,徐延宁.参数化设计研究[J].计算机辅助设计与图形学学报,2002,14(11)：1086-1090.
[158]明冬萍,骆剑承,沈占锋等.高分辨率遥感影像信息提取与目标识别技术研究[J].测绘科学,2005,30(3)：18-20.
[159]冉琼,迟耀斌,王智勇等.基于“北京一号”小卫星影像阴影的建筑物高度测算研究[J].遥感信息,2008(4)：18-21.
[160]任自珍,岑敏仪,张同刚等LiDAR数据中建筑物提取的新方法-Fc-S法[J].测绘科学,2010,35(6)：134-136,141.
[161]阮秋琦.数字图像处理学[M],北京：电子工业出版社,2001：390.
[162]萨师炬,王珊.数据库系统概论[G],北京：高等教育出版社,2004.
[163]邵巨良.小波理论——影像分析与目标识别[M]：武汉测绘科技大学出版社,1993：162.
[164]邵振峰.基于航空立体影像对的人工目标三维提取与重建[D].博士学位论文：武汉大学,2004.
[165]沈蔚,李京,陈云浩等.基于LIDAR数据的建筑轮廓线提取及规则化算法研究[J].遥感学报,2008,12(5)：692-698.
[166]沈文.”参数化主义”的崛起——新建筑时代的到来[J].城市环境设计,2010(8)：194-199.
[167]沈掌泉,王人潮.基于拓扑关系原理的栅格转换矢量方法的研究[J].遥感学报,1999,3(1)：38-42.
[168]宋世军,石来德,乔彩凤.运动人体图像分割算法研究[J].中国工程机械学报,2007,7(5)：16-21.
[169]孙善芳.从航空影像提取城区表面信息[D].博士学位论文：武汉测绘科技大学武汉大学,1994.
[170]谭衢霖,王今飞.结合高分辨率多光谱影像和LiDAR数据提取城区建筑[J].应用基础与工程科学学报,2011,19(5)：741-748.
[171]唐亮.城市航空影像关键地物提取技术研究[D].博士学位论文：西安电子科技大学,2004.
[172]唐亮,谢维信,黄建军等.从航空影像中自动提取高层建筑物[J].计算机学报,2005,28(7)：1199-1204.
[173]陶闯.从大比例尺黑白航空影象提取地物信息----一种基于人机协同的目标导引技术[D].硕士学位论文：武汉测绘科技大学武汉大学,1993.
[174]陶金花,苏林,李树楷.一种从激光雷达点云中提取建筑物模型的方法[J].红外与激光工程,2009,38(2)：340-345.
[175]陶文兵,柳健,田金文.一种新型的航空图像城区建筑物自动提取方法[J].计算机学报,2003,26(7)：866-873.
[176]田新光,张继贤,张永红.利用QuickBird影像的阴影提取建筑物高度[J].测绘科学,2008,33(2)：88-89,77.
[177]宛延琦.工程数据库系统[G],北京：清华大学出版社,1999.
[178]万剑华.城市3维地理信息系统的建模研究[D],武汉：武汉大学,2001.
[179]王爱民,沈兰荪.图像分割研究综述[J].测控技术,2000,19(5)：1-7.
[180]王继周,李成名.城市景观三维模型库的原理、构建及应用[J].测绘科学,2007,32(4)：20-22.
[181]王家耀,宁津生,张祖勋.中国数字城市建设方案及推进战略研究[M].北京：科学出版社,2008.
[182]王健,靳奉祥,李云岭等.三维激光扫描技术在城市三维数字景观建模中的应用[c]：2008年测绘科学前沿技术论坛,南京,2008.
[183]王俊,朱利.基于图像匹配-点云融合的建筑物立面三维重建[J].计算机学报,2012,35(10)：2072-2079.
[184]王丽英.城市环境的过程式建模技术研究[D].博士学位论文：浙江大学计算机科学学院浙江大学,2009.
[185]王伟,黄雯雯,镇姣Pictometry倾斜摄影技术及其在3维城市建模中的应用[J].测绘与空间地理信息,2011,34(3)：181-183.
[186]王永会,王勇勇,王守金.基于TIN和CSG的三维城市建模方法[J].沈阳建筑大学学报(自然科学版),2012,28(3)：563-568.
[187]翁姝.区域建筑物三维重建技术与实现[D].硕士学位论文：华中师范大学,2011.
[188]吴慧欣,薛惠锋,邢书宝.限定TIN与CSG集成仿真模型生成算法研究[J].计算机应用,2007,27(2)：475-478.
[189]吴晶晶.“十二五”期间我国全部地级市将建成数字城市[EB/OL].http://www.gov.cn/jrzg/2012-09/10/content_2221342.htm.
[190]吴静,靳奉祥,王健.基于三维激光扫描数据的建筑物三维建模[J].测绘工程,2007, 16(5)：57-60.
[191]吴军.3维城市建模中的建筑墙面纹理快速重建研究[J].测绘学报,2005,34(4)：317-323.
[192]吴秦.STL之Map[EB/OL]. http://www.cnblogs.com/skynet/archive/2010/06/18/1760518.html.
[193]夏春林,王佳奇3DGIS中建筑物三维建模技术综述[J].测绘科学,2011,36(1)：70-72.
[194]谢军飞,李延明.利用IKONOS卫星图像阴影提取城市建筑物高度信息[J].国土资源遥感,2004(4)：4-6.
[195]谢顺平,都金康,王结臣.实现栅格图形和图像数据矢量化提取的游程轮廓追踪法[J].遥感学报,2004,8(5)：465-470.
[196]谢亦才,李岩Douglas-Peucker算法在无拓扑矢量数据压缩中的改进[J].计算机工程与应用,2009,45(32)：189-192.
[197]辛大永.建设工程竣工验收建筑高度测量几点问题的探讨[J].黑龙江科技信息,2010(6)：260.
[198]徐丰.参数化城市主义——一个理解城市的新的角度[J].城市建筑,2010(6)：47-50.
[199]徐丰,金亚秋.多方位高分辨率SAR的三维目标自动重建(二)多方位重建[J].电波科学学报,2008,23(1)：23-33.
[200]徐明霞.三维城市景观建模技术在小区规划中的应用[D].硕士学位论文：长安大学,2006.
[201]薛强,张志强,孙济渊.一种用于建筑物场景重建的方法[J].计算机工程,2004,30(6)：179-181.
[202]杨得志,王杰臣,闾国年.矢量数据压缩的Douglas-Peucker算法的实现与改进[J].测绘通报,2002(7)：18-19.
[203]杨建宇,杨崇俊,明冬萍等WebGIS系统中矢量数据的压缩与化简方法综述[J].计算机工程与应用,2004,40(32)：36-38,92.
[204]杨长江,陈冲.再论建筑物高度的测量方法[J].测绘通报,2005(8)：47-48.
[205]叶齐祥,高文,王伟强等.一种融合颜色和空间信息的彩色图像分割算法[J].软件学报,2004(4)：522-530.
[206]尹平,王润生.基于边缘信息的分开合并图像分割算法[J].中国图象图形学报,1998,3A(6)：450-454.
[207]尤红建.激光三维遥感数据处理及建筑物重建[M].北京：测绘出版社,2006.
[208]游亚鹏,杨剑雷.“参数化实现”设计的一个建筑实例杭州奥体中心体育游泳馆[J].城市环境设计,2012(4)：240-251.
[209]虞自奋.属性块在工程图形中的研究与应用[J].天津冶金,2008(3)：28-30.
[210]袁晓辉,金立左,李久贤等.基于兴趣区检测与分析的水上桥梁识别[J].红外与毫米波学报,2003,22(5)：331-336.
[211]张桂芳,单新建,尹京苑等.单幅高空间分辨率卫星图像提取建筑物三维信息的方法研究[J].地震地质,2007,29(1)：180-187.
[212]张昊LIDAR建筑物提取方法研究[D].硕士学位论文：中国民航大学,2007.
[213]张卡,盛业华,李永强等.基于数字近景立体摄影的三维表面模型构建[J].数据采集与处理,2007,22(3)：309-314.
[214]张鹏,李伟,胡诚轶.城市高层建筑物高度的检测方法之一——悬高测量法[J].科技信息(学术版),2008(12)：269-272.
[215]张平,王文伟,吴丽芸.基于均匀性图分水岭变换及两步区域合并的彩色图像分割[J].计算机应用,2006(6)：1378-1380.
[216]张莎莎.图像分割与运动目标跟踪算法研究[D],哈尔滨：哈尔滨工业大学,2006.
[217]张树有,彭群生,谭建荣.基于空间基坐标的尺寸可标注性判别研究[J].计算机学报,2000,23(9)：982-986.
[218]张颖,吴成东,原宝龙.机器人路径规划方法综述[J].控制工程,2003,10增刊：152-154.
[219]张煜,张祖勋,张剑清.几何约束与影像分割相结合的快速半自动房屋提取[J].武汉测绘科技大学学报,2000,25(3)：238-242.
[220]章孝灿,潘云鹤.GIS中基于“栅格技术”的栅格数据矢量化技术[J].计算机辅助设计与图形学学报,2001,13(10)：895-900.
[221]章毓晋.图像分割[M].北京：科学出版社,2001.
[222]赵斌.高层建筑施工GPS测量技术分析[J].科技资讯,2010(19)：93.
[223]赵锦艳.建筑图重建技术及其模型信息提取方法的研究[J].湖南工业大学学报,2009,23(4)：41-44.
[224]赵锦艳,刘任任,王兆其等.一种基于抽象语义识别的交互式三维建筑物重建系统[C]：第七届全国虚拟现实与可视化学术会议,北京,2007.
[225]赵俊娟,尹京苑,单新建.基于高分辨率卫星影像的建筑物轮廓矢量化技术[J].防灾减灾工程学报,2004,24(2)：153-157.
[226]周俊,晏非,孙曼.基于区域分割合并的建筑物半自动提取方法[J].海洋测绘,2005,25(1)：58-60.
[227]周亚男,沈占锋,骆剑承等.阴影辅助下的面向对象城市建筑物提取[J].地理与地理信息科学,2010,26(3)：37-40.
[228]朱国敏,马照亭,孙隆祥等.城市三维地理信息系统中三维模型的快速构建方法[J].地理与地理信息科学,2007,23(4)：29-32,40.
[229]左建章,关艳玲,朱强.大范围三维城市立体景观建模系统的研究[J].测绘科学,2005,30(2)：22-24.