LEE- Geomatik Mühendisliği-Doktora
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ÖgeA semi-automatic façade generation methodology of architectural heritage from laser point clouds: A case study on Architect Sinan(Lisansüstü Eğitim Enstitüsü, 2021) Kıvılcım, Cemal Özgür ; Duran, Zahide ; 709850 ; Geomatik MühendisliğiTangible cultural assets from different periods and civilizations reinforce historical and cultural memories that are passed from generation to generation. However, due to natural events, lack of proper maintenance, or wars, the heritage structures can be damaged or destroyed over time. To preserve tangible cultural assets for the future, it is crucial to ensure that these buildings' maintenance, repair, and restoration are of high quality. Hence, the preliminary phase in any architectural heritage project is to obtain metric measurements and documentation of the building and its individual elements. In this direction, the acquired data and derived models are used for various purposes in the fields of engineering and architectural applications, digital modeling and reconstructions, virtual or augmented reality applications. However, conventional measurement techniques require tremendous resources and lengthy project completion time for architectural surveys and 3D model production. With technological advances, laser scanning systems became a preferred technology as a geospatial data acquisition technique in the heritage documentation process. Without any doubt, these systems provide many advantages over conventional measurement techniques since the data acquisition is carried out effectively and in a relatively short time. On the other hand, obtaining final products from point clouds is generally time-consuming and requires data manipulation expertise. To achieve this, the operator, who has the knowledge about the structure, must interpret the point cloud, select the key points representing the underlying geometry and perform the vectorizing process over these points. In addition, point data contains systematic and random errors. The noisy point cloud data and ambiguities make this process tedious and prone to human error. The purpose of this thesis is to reduce the user's manual work cycle burden in obtaining 3D models and products from point cloud data: A semi-automatic user-guided methodology with few interventions is developed to easily interpret the geometry of architectural elements and establish fundamental semantic relationships from complex, noisy point clouds. First, the conventional workflow and methodologies in cultural heritage documentation were researched, and the bottlenecks of the current workflow were examined. Then, existing methodologies used in point cloud-based 3D digital building reconstruction were assessed. From this, semi-automatic methods are evaluated for a more suitable approach to 3D digital reconstruction of cultural heritage assets, which are more complex than modern buildings. Recently, Building Information Modeling (BIM) process applications have gained momentum. BIM systems make many contributions to project management, from the design to the operation of new modern buildings. Research on the applications for existing buildings in BIM has increased. Particularly, such applications and research in cultural heritage are gathered under the term of Heritage/Historic-Building Information Modeling (HBIM). In HBIM, dedicated architectural style libraries are generated, and geometric models are produced by associating the geometries of architectural elements with point clouds. Such applications generally come for Western architectural elements, in which construction techniques and geometrical relations of architectural rules and orders have been documented with sketches and drawings for centuries. Detailed descriptions and fine sketches pertaining to the rules and style studies of Ottoman architecture are limited. Having been the capital of many civilizations, historic Istanbul is crowned with the many mosques of Architect Sinan, dating from the 16th century, the golden era of the Ottoman Empire. For his innovative structures, Architect Sinan is considered an architectural and engineering genius. Unfortunately, Sinan did not leave enough written or visual documentation of his works, and although many aspects of Sinan's works have been researched, few have worked on the geometry of the facade elements. Previous architectural research examines the ratios and compares the general architectural elements of Sinan's works (comparing the dimensions and location of the elements). Building on this and our observations of Sinan's mosques, we designed an object-oriented library of parametric objects for selected architectural facade elements. In addition, some fundamental semantic relations of the prepared object library elements were introduced. A case study for procedural modeling was then carried out. In the next stage, we evaluated that an algorithmic approach can be used to obtain parametric architectural elements from noisy point cloud data. We benefited from the Random Sample Consensus (RANSAC) algorithm, which has a wide range of applications in computer vision and robotics. The algorithm is based on the purpose of obtaining the parameters of a given mathematical model; it is a non-deterministic method based on selecting the required number of random data from the data set to create the model and measuring the extent to which the hypothesis produced is compatible with the entire data set by evaluating the model. The basics of this method work with a certain number of iterations and return outputs of the most suitable model parameters, the dataset that makes up the model, and the incompatible data. In addition, model-specific criteria and rules based on architectural knowledge were added to the developed methodology to reduce the number of iterations. All algorithmic codes were produced in Python language. In addition, we used libraries such as NumPy and for arrays and mathematical operations. For visualization studies, the open graphics library (Open Graphics Library, OpenGL) was carried out using the Visualization Tool Kit (VTK) on the graphics application development interface. In addition, python modules of VTK C++ source libraries were compiled using CMake software and Microsoft Visual Studio. As the application area of the study, one of the most important mosques of Istanbul Şehzade Mosque, which is Mimar Sinan's first selatin complex, was chosen. Point cloud data acquired with a terrestrial laser scanner for the documentation studies of the mosque was obtained for this study. Different case areas were determined from the point cloud datasets. Windows on the Qibla direction façade and the domes from the roof covering of the mosque were used, respectively. While making this choice, we considered the variety of window elements and Sinan's use of the dome influenced. In the case applications, the point cloud selected from the window areas was segmented semi-automatically using proposed method recursively at different window levels from the inside to the outside. In the other case study, the algorithm performed the segmentation of the main dome. As a result of this segmentation, point groups that are not included in the model are evaluated once more time using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm from Python's scikit-learn and presented to the user as a guiding output in the determination of architectural elements and deformations. Using the above-mentioned Sinan architectural dome typology relations with the main dome of the mosque, it was ensured that point clusters were formed in the modeling of other dome structures in the mosque. Finally, as an example, the parametric dome model was converted to Industry Foundation Class (IFC) format using open source CAD software. Integrity and accuracy comparisons were made using the outputs of the presented methodology and the CAD drawings produced by the restoration architects using the same data. The results were within acceptable limits for general-scale studies. Additionally, the presented method contributed to the interpretation of the data by saving time for expert users. In summary, a method has been developed for the semi-automatic extraction of architectural parametric models working directly on the 3D point cloud, specific to the Ottoman Classical Era Mosque, particularly Architect Sinan's works, using a data and model-oriented hybrid 3D building reconstruction approach.