Archaeological Building Information Modeling: beyond scalable representation of architecture and archaeology

The widespread use of technologies and processes aimed at information management is one of the main trends in today’s building industry. Collaboration, coordination and validation of design results are fostered by software and workflows that involve many disciplines. Taking into account these premises, this paper deals with the application of such a paradigm to the archaeological and architectural fields. The application to the particular case study of the Etruscan town of Kainua aspires to be exemplary, since it is referred to different metric scales, from the building to the urban settlement. The digital reconstruction of the whole town, which can be explored and studied by means of Virtual Reality, was validated from a philological point of view using an original interdisciplinary approach called ArchaeoBIM, i.e. a methodology that encompasses the information flow among different disciplines with the same interest in understanding, and virtually reconstructing, lost realities. Using this method, architectural proportions brought by existing literature, physical behaviours of materials and components, layouts of rooms and spaces regulated by rituals or historic traditions are collected in a model that is able to represent morphologies, analysis and functions. This model, basically a geometric database linking heterogeneous documents, can be used in many different ways, from analytic abstractions to static simulations, from solar analysis to visual renderings. It becomes a common language for information exchange among scholars and users interested in the dissemination and study of the cultural heritage

Toward knowledge-based automatic 3D spatial topological modeling from LiDAR point clouds for urban areas

Le traitement d'un très grand nombre de données LiDAR demeure très coûteux et nécessite des approches de modélisation 3D automatisée. De plus, les nuages de points incomplets causés par l'occlusion et la densité ainsi que les incertitudes liées au traitement des données LiDAR compliquent la création automatique de modèles 3D enrichis sémantiquement. Ce travail de recherche vise à développer de nouvelles solutions pour la création automatique de modèles géométriques 3D complets avec des étiquettes sémantiques à partir de nuages de points incomplets. Un cadre intégrant la connaissance des objets à la modélisation 3D est proposé pour améliorer la complétude des modèles géométriques 3D en utilisant un raisonnement qualitatif basé sur les informations sémantiques des objets et de leurs composants, leurs relations géométriques et spatiales. De plus, nous visons à tirer parti de la connaissance qualitative des objets en reconnaissance automatique des objets et à la création de modèles géométriques 3D complets à partir de nuages de points incomplets. Pour atteindre cet objectif, plusieurs solutions sont proposées pour la segmentation automatique, l'identification des relations topologiques entre les composants de l'objet, la reconnaissance des caractéristiques et la création de modèles géométriques 3D complets. (1) Des solutions d'apprentissage automatique ont été proposées pour la segmentation sémantique automatique et la segmentation de type CAO afin de segmenter des objets aux structures complexes. (2) Nous avons proposé un algorithme pour identifier efficacement les relations topologiques entre les composants d'objet extraits des nuages de points afin d'assembler un modèle de Représentation Frontière. (3) L'intégration des connaissances sur les objets et la reconnaissance des caractéristiques a été développée pour inférer automatiquement les étiquettes sémantiques des objets et de leurs composants. Afin de traiter les informations incertitudes, une solution de raisonnement automatique incertain, basée sur des règles représentant la connaissance, a été développée pour reconnaître les composants du bâtiment à partir d'informations incertaines extraites des nuages de points. (4) Une méthode heuristique pour la création de modèles géométriques 3D complets a été conçue en utilisant les connaissances relatives aux bâtiments, les informations géométriques et topologiques des composants du bâtiment et les informations sémantiques obtenues à partir de la reconnaissance des caractéristiques. Enfin, le cadre proposé pour améliorer la modélisation 3D automatique à partir de nuages de points de zones urbaines a été validé par une étude de cas visant à créer un modèle de bâtiment 3D complet. L'expérimentation démontre que l'intégration des connaissances dans les étapes de la modélisation 3D est efficace pour créer un modèle de construction complet à partir de nuages de points incomplets.The processing of a very large set of LiDAR data is very costly and necessitates automatic 3D modeling approaches. In addition, incomplete point clouds caused by occlusion and uneven density and the uncertainties in the processing of LiDAR data make it difficult to automatic creation of semantically enriched 3D models. This research work aims at developing new solutions for the automatic creation of complete 3D geometric models with semantic labels from incomplete point clouds. A framework integrating knowledge about objects in urban scenes into 3D modeling is proposed for improving the completeness of 3D geometric models using qualitative reasoning based on semantic information of objects and their components, their geometric and spatial relations. Moreover, we aim at taking advantage of the qualitative knowledge of objects in automatic feature recognition and further in the creation of complete 3D geometric models from incomplete point clouds. To achieve this goal, several algorithms are proposed for automatic segmentation, the identification of the topological relations between object components, feature recognition and the creation of complete 3D geometric models. (1) Machine learning solutions have been proposed for automatic semantic segmentation and CAD-like segmentation to segment objects with complex structures. (2) We proposed an algorithm to efficiently identify topological relationships between object components extracted from point clouds to assemble a Boundary Representation model. (3) The integration of object knowledge and feature recognition has been developed to automatically obtain semantic labels of objects and their components. In order to deal with uncertain information, a rule-based automatic uncertain reasoning solution was developed to recognize building components from uncertain information extracted from point clouds. (4) A heuristic method for creating complete 3D geometric models was designed using building knowledge, geometric and topological relations of building components, and semantic information obtained from feature recognition. Finally, the proposed framework for improving automatic 3D modeling from point clouds of urban areas has been validated by a case study aimed at creating a complete 3D building model. Experiments demonstrate that the integration of knowledge into the steps of 3D modeling is effective in creating a complete building model from incomplete point clouds

CityGML in the Integration of BIM and the GIS: Challenges and Opportunities

CityGML (City Geography Markup Language) is the most investigated standard in the integration of building information modeling (BIM) and the geographic information system (GIS), and it is essential for digital twin and smart city applications. The new CityGML 3.0 has been released for a while, but it is still not clear whether its new features bring new challenges or opportunities to this research topic. Therefore, the aim of this study is to understand the state of the art of CityGML in BIM/GIS integration and to investigate the potential influence of CityGML3.0 on BIM/GIS integration. To achieve this aim, this study used a systematic literature review approach. In total, 136 papers from Web of Science (WoS) and Scopus were collected, reviewed, and analyzed. The main findings of this review are as follows: (1) There are several challenging problems in the IFC-to-CityGML conversion, including LoD (Level of Detail) mapping, solid-to-surface conversion, and semantic mapping. (2) The ‘space’ concept and the new LoD concept in CityGML 3.0 can bring new opportunities to LoD mapping and solid-to-surface conversion. (3) The Versioning module and the Dynamizer module can add dynamic semantics to the CityGML. (4) Graph techniques and scan-to-BIM offer new perspectives for facilitating the use of CityG

MODELLING IN HBIM TO DOCUMENT MATERIALS DECAY BY A THEMATIC MAPPING TO MANAGE THE CULTURAL HERITAGE: THE CASE OF "CHIESA DELLA PIETÀ" IN FERMO

Abstract. Relevant, historically, it is the role of the Diocese of Fermo (Italy) in the Vatican organization dedicated to vast ecclesiastical patrimony on the territory of the Marche region. In this context, for the peculiarity of its identity and its property, the object of this study is the "Chiesa della Pietà". This research starts with the photogrammetric survey to document and analyse the existing condition of the church. The data acquisition provides many scans following a network schema and the photographic survey allows to create orthoimages to make more realistic the 3D representation. Once acquired the geometric and material survey, a series of investigations have been carried out to assess the surface degradation and the material decay of the external façades and internal environments. Furthermore, some structural problems have been occurred, investigating and verifying the presence of advanced stages of deterioration of the wooden structures and the restoration of these structural elements must be mandatory. To take under control the decay and to propose a restoration step, we have arranged the 3D model in HBIM software with different LOD, according to the BIM Forum Level of Development Specification (2016), suitable to develop a well-structured information system. Before the 3D modelling phase, a decomposition of the building is useful to implement a semantic classification of the architectural elements. Basing on a hierarchy of classes and subclasses, the dedicated database organizes the building components assigning an ID-code to the features, putting in evidence materials decay by a thematic mapping.</p

A state-of-the-art review of built environment information modelling (BeIM)

Elements that constitute the built environment are vast and so are the independent systems developed to model its various aspects. Many of these systems have been developed under various assumptions and approaches to execute functions that are distinct, complementary or sometimes similar. Also, these systems are ever increasing in number and often assume similar nomenclatures and acronyms thereby exacerbating the challenges of understanding their peculiar functions, definitions and differences. The current societal demand to improve sustainability performance through collaboration, whole-systems and through-life thinking, is driving the need to integrate independent systems associated with different aspects and scales of the built environment to deliver smart solutions and services that improve the wellbeing of citizens. The contemporary object-oriented digitization of real world elements appears to provide a leeway for amalgamating modelling systems of various domains in the built environment which we termed as built environment information modelling (BeIM). These domains included Architecture, Engineering, Construction and Urban Planning and Design. Applications such as Building Information Modelling, Geographic Information Systems and 3D City Modelling systems are now being integrated for city modelling purposes. The various works directed at integrating these systems are examined revealing that current research efforts on integration fall into three categories: (1) data/file conversion systems, (2) semantic mapping systems and (3) the hybrid of both. The review outcome suggests that a good knowledge of these domains and how their respective systems operate is vital to pursuing holistic systems integration in the built environment

Combining visibility analysis and deep learning for refinement of semantic 3D building models by conflict classification

Semantic 3D building models are widely available and used in numerous applications. Such 3D building models display rich semantics but no façade openings, chiefly owing to their aerial acquisition techniques. Hence, refining models’ façades using dense, street-level, terrestrial point clouds seems a promising strategy. In this paper, we propose a method of combining visibility analysis and neural networks for enriching 3D models with window and door features. In the method, occupancy voxels are fused with classified point clouds, which provides semantics to voxels. Voxels are also used to identify conflicts between laser observations and 3D models. The semantic voxels and conflicts are combined in a Bayesian network to classify and delineate façade openings, which are reconstructed using a 3D model library. Unaffected building semantics is preserved while the updated one is added, thereby upgrading the building model to LoD3. Moreover, Bayesian network results are back-projected onto point clouds to improve points’ classification accuracy. We tested our method on a municipal CityGML LoD2 repository and the open point cloud datasets: TUM-MLS-2016 and TUM-FAÇADE. Validation results revealed that the method improves the accuracy of point cloud semantic segmentation and upgrades buildings with façade elements. The method can be applied to enhance the accuracy of urban simulations and facilitate the development of semantic segmentation algorithms

Semantic Instance Annotation of Street Scenes by 3D to 2D Label Transfer

Semantic annotations are vital for training models for object recognition, semantic segmentation or scene understanding. Unfortunately, pixelwise annotation of images at very large scale is labor-intensive and only little labeled data is available, particularly at instance level and for street scenes. In this paper, we propose to tackle this problem by lifting the semantic instance labeling task from 2D into 3D. Given reconstructions from stereo or laser data, we annotate static 3D scene elements with rough bounding primitives and develop a model which transfers this information into the image domain. We leverage our method to obtain 2D labels for a novel suburban video dataset which we have collected, resulting in 400k semantic and instance image annotations. A comparison of our method to state-of-the-art label transfer baselines reveals that 3D information enables more efficient annotation while at the same time resulting in improved accuracy and time-coherent labels.Comment: 10 pages in Conference on Computer Vision and Pattern Recognition (CVPR), 201

Current State of the Art Historic Building Information Modelling

In an extensive review of existing literature a number of observations were made in relation to the current approaches for recording and modelling existing buildings and environments: Data collection and pre-processing techniques are becoming increasingly automated to allow for near real-time data capture and fast processing of this data for later modelling applications. Current BIM software is almost completely focused on new buildings and has very limited tools and pre-defined libraries for modelling existing and historic buildings. The development of reusable parametric library objects for existing and historic buildings supports modelling with high levels of detail while decreasing the modelling time. Mapping these parametric objects to survey data, however, is still a time-consuming task that requires further research. Promising developments have been made towards automatic object recognition and feature extraction from point clouds for as-built BIM. However, results are currently limited to simple and planar features. Further work is required for automatic accurate and reliable reconstruction of complex geometries from point cloud data. Procedural modelling can provide an automated solution for generating 3D geometries but lacks the detail and accuracy required for most as-built applications in AEC and heritage fields

Geospatial Information Research: State of the Art, Case Studies and Future Perspectives

Geospatial information science (GI science) is concerned with the development and application of geodetic and information science methods for modeling, acquiring, sharing, managing, exploring, analyzing, synthesizing, visualizing, and evaluating data on spatio-temporal phenomena related to the Earth. As an interdisciplinary scientific discipline, it focuses on developing and adapting information technologies to understand processes on the Earth and human-place interactions, to detect and predict trends and patterns in the observed data, and to support decision making. The authors – members of DGK, the Geoinformatics division, as part of the Committee on Geodesy of the Bavarian Academy of Sciences and Humanities, representing geodetic research and university teaching in Germany – have prepared this paper as a means to point out future research questions and directions in geospatial information science. For the different facets of geospatial information science, the state of art is presented and underlined with mostly own case studies. The paper thus illustrates which contributions the German GI community makes and which research perspectives arise in geospatial information science. The paper further demonstrates that GI science, with its expertise in data acquisition and interpretation, information modeling and management, integration, decision support, visualization, and dissemination, can help solve many of the grand challenges facing society today and in the future

Proceedings. 9th 3DGeoInfo Conference 2014, [11-13 November 2014, Dubai]

It is known that, scientific disciplines such as geology, geophysics, and reservoir exploration intrinsically use 3D geo-information in their models and simulations. However, 3D geo-information is also urgently needed in many traditional 2D planning areas such as civil engineering, city and infrastructure modeling, architecture, environmental planning etc. Altogether, 3DGeoInfo is an emerging technology that will greatly influence the market within the next few decades. The 9th International 3DGeoInfo Conference aims at bringing together international state-of-the-art researchers and practitioners facilitating the dialogue on emerging topics in the field of 3D geo-information. The conference in Dubai offers an interdisciplinary forum of sub- and above-surface 3D geo-information researchers and practitioners dealing with data acquisition, modeling, management, maintenance, visualization, and analysis of 3D geo-information