Building acquisition, textured building models, integration of GIS-technology and image analysis

该项目的目的是开发模型，方法和工具，用于3D城市模型的半自动，交互式细化。从细节层次2（LOD 2）的模型开始，由简单的建筑块和屋顶结构组成，细化导致LOD 3的模型，即具有地面边缘、楼梯、阳台、窗户、门和纹理的详细建筑模型。重点是建筑立面和数字立面模型之间的过渡，即所谓的建筑衣领。其主要组成部分是一个三维空间数据库，其中集成了矢量建筑模型以及航空和地面光栅图像。一个精心设计的用户界面支持在图像的解释歧义的互动解决方案。对于几何和纹理的整合，将开发一个评价函数，该评价函数平衡了模型和图像之间在视觉可接受性方面不可分割的冲突。在第一阶段，我们已经开发了一个本体，工作流程方案，通用模型和程序重建楼梯作为地形和建筑物之间的主要联系。在第二阶段，我们专注于更一般的部分，建设衣领，整合到一个互动的系统，特别是使用随机文法，贝叶斯网络，也可能马尔可夫随机场和蒙特卡洛技术的可靠恢复的基本结构。该方法的新奇之处在于：（1）高分辨率对象模型的规范，（2）从地理参考点云重建实例化对象模型，并根据模型规范进行泛化。(3)综合使用随机属性文法和图像解释的图形模型。

The aim of the project is to develop models, methods, and tools for the semi-automatic, interactive refinement of 3D city models. Starting from models of level of detail 2 (LOD2), consisting of simple building blocks and roof structures, the refinement leads to models of LOD3, namely detailed building models with ground edges, stairs, balconies, windows, doors and textures. Focus is on the transition between building facades and the digital elevation model, the so-called building collar. The main component is a 3D spatial database which integrates vector building models and aerial and terrestrial raster images. A carefully designed user interface supports the interactive resolution of ambiguities in the interpretation of the images. For the integration of geometry and texture an evaluation function will be developed which balances the inextricable conflict between model and image with respect to visual plausibility. In the first phase we have developed an ontology, work flow scenarios, generic models and procedures for reconstructing stairs as the main link between the terrain and a building. In the second phase we focus on more general parts of the building collar, on the integration into an interactive system, especially using stochastic grammars, Bayesian networks, possibly also Markov-Random fields and Monte Carlo techniques for a reliable recovery of essential structures. The novelty of the approach is (1) the specification of high resolution object models, (2) the reconstruction of the instantiated object model from geo-referenced point clouds and its generalization according to the model specification. (3) the integrated use of stochastic attribute grammars and graphical models for image interpretation.