@article{ChizhovaBrunnStilla, author = {Chizhova, Maria and Brunn, Ansgar and Stilla, Uwe}, title = {Probabilistic feasibility of the HE reconstruction process of russian-orthodox churches}, series = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, volume = {XLI-B5}, journal = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, doi = {https://doi.org/10.5194/isprs-archives-XLI-B5-221-2016}, pages = {221 -- 227}, abstract = {The cultural human heritage is important for the identity of following generations and has to be preserved in a suitable manner. In the course of time a lot of information about former cultural constructions has been lost because some objects were strongly damaged by natural erosion or on account of human work or were even destroyed. It is important to capture still available building parts of former buildings, mostly ruins. This data could be the basis for a virtual reconstruction. Laserscanning offers in principle the possibility to take up extensively surfaces of buildings in its actual status. In this paper we assume a priori given 3d-laserscanner data, 3d point cloud for the partly destroyed church. There are many well known algorithms, that describe different methods of extraction and detection of geometric primitives, which are recognized separately in 3d points clouds. In our work we put them in a common probabilistic framework, which guides the complete reconstruction process of complex buildings, in our case russian-orthodox churches. Churches are modeled with their functional volumetric components, enriched with a priori known probabilities, which are deduced from a database of russian-orthodox churches. Each set of components represents a complete church. The power of the new method is shown for a simulated dataset of 100 russian-orthodox churches.}, language = {en} } @article{ChizhovaGurianovHessetal., author = {Chizhova, Maria and Gurianov, Andrey and Hess, Mona and Luhmann, Thomas and Brunn, Ansgar and Stilla, Uwe}, title = {Semantic segmentation of building elements using point cloud hashing}, series = {ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, volume = {VLII-2}, journal = {ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, doi = {https://doi.org/10.5194/isprs-archives-XLII-2-241-2018}, pages = {241 -- 250}, abstract = {For the interpretation of point clouds, the semantic definition of extracted segments from point clouds or images is a common problem. Usually, the semantic of geometrical pre-segmented point cloud elements are determined using probabilistic networks and scene databases. The proposed semantic segmentation method is based on the psychological human interpretation of geometric objects, especially on fundamental rules of primary comprehension. Starting from these rules the buildings could be quite well and simply classified by a human operator (e.g. architect) into different building types and structural elements (dome, nave, transept etc.), including particular building parts which are visually detected. The key part of the procedure is a novel method based on hashing where point cloud projections are transformed into binary pixel representations. A segmentation approach released on the example of classical Orthodox churches is suitable for other buildings and objects characterized through a particular typology in its construction (e.g. industrial objects in standardized enviroments with strict component design allowing clear semantic modelling).}, language = {en} } @article{ChizhovaKorovinGurianovetal., author = {Chizhova, Maria and Korovin, Dmitriyi and Gurianov, Andrey and Brodovskii, Maxim and Brunn, Ansgar and Stilla, Uwe and Luhmann, Thomas}, title = {Probabilistic Reconstruction of orthodox Churches from precision Point Clouds using Bayesian Networks and Cellular Automata}, series = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, volume = {VLII-2/W3}, journal = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, doi = {doi:10.5194/isprs-archives-XLII-2-W3-187-2017}, pages = {187 -- 194}, abstract = {The point cloud interpretation and reconstruction of 3d-buildings from point clouds has already been treated for a few decades. There are many articles which consider the different methods and workows of the automatic detection and reconstruction of geometrical objects from point clouds. Each method is suitable for the special geometry type of object or sensor. General approaches are rare. In our work we present an algorithm which develops the optimal process sequence of the automatic search, detection and reconstruction of buildings and building components from a point cloud. It can be used for the detection of the set of geometric objects to be reconstructed, independent of its destruction. In a simulated example we reconstruct a complete Russian-orthodox church starting from the set of detected structural components and reconstruct missing components with high probability.}, language = {en} } @inproceedings{MeyerBrunnStilla, author = {Meyer, Theresa and Brunn, Ansgar and Stilla, Uwe}, title = {Genauigkeitsbetrachtung voxelbasierter {\"A}nderungsdetektion im Geb{\"a}udeinnenbereich zur automatisierten Baufortschritts{\"u}berwachung}, series = {Publikationen der Deutschen Gesellschaft f{\"u}r Photogrammetrie, Fernerkundung und Geoinformation e.V.}, volume = {30}, booktitle = {Publikationen der Deutschen Gesellschaft f{\"u}r Photogrammetrie, Fernerkundung und Geoinformation e.V.}, doi = {10.24407/KXP:1796028584}, abstract = {Dieser Beitrag handelt von einer Methode zur {\"A}nderungsdetektion im Geb{\"a}udeinneren, die auf der Diskretisierung des Objektraums durch Voxel basiert. Die Belegung des Voxelraums wird anhand von Punktwolken aus terrestrischem Laserscanning zu verschiedenen Bauphasen ermittelt. Durch die Aufdeckung von Belegungskonflikten zwischen zwei Messepochen wird ermittelt, ob {\"A}nderungen an einer bestimmten Stelle aufgetreten sind. Es wird gezeigt, wie sich der Diskretisierungsfehler als Resultat der Voxelisierung auf die noch erreichbare r{\"a}umliche Aufl{\"o}sung einer {\"A}nderungsaussage auswirkt. Am Beispiel von Abbrucharbeiten bei einem Innenumbauprojekt werden die wechselseitigen Auswirkungen von Aufnahmegeometrie, Scanaufl{\"o}sung und Voxelgr{\"o}ße diskutiert. Die Ergebnisse zeigen, dass die Aufl{\"o}sung von 3D-Punktwolken unter Beachtung einiger Anforderungen an die Aufnahmegeometrie bei Innenraum-Messungen ausreicht, um bei g{\"a}ngigen Genauigkeitsanforderungen auf Voxelebene automatisiert strukturelle {\"A}nderungen zu beschreiben.}, language = {de} } @inproceedings{ChizhovaGurianovKorovinetal., author = {Chizhova, Maria and Gurianov, Andrey and Korovin, Dmitrii and Brunn, Ansgar and Stilla, Uwe}, title = {Automatically Extraction and Reconstruction of Cupola Geometries of Orthodox Churches from Precision Point Clouds}, series = {37. Wissenschaftlich-Technische Jahrestagung der DGPF in W{\"u}rzburg - Publikationen der DGPF}, booktitle = {37. Wissenschaftlich-Technische Jahrestagung der DGPF in W{\"u}rzburg - Publikationen der DGPF}, number = {26}, pages = {434 -- 443}, abstract = {Complex geometry extraction from point clouds is an actual problem in reverse engineering. Simple geometrical models (like parallelepipeds, prisms, pyramids, cones, spheres) were already applied in construction and machine-building modeling, but are not sufficient for high quality BIM now. This work, which is carried out in the context of virtual reconstruction of destroyed orthodox churches, presents a robust and efficient method of cupola (domes) and tambour geometry extraction from precise point clouds. The rich diversity of architectural forms, which are defined by many parameters, does not allow to consider this problem as a trivial duty, because usual geometry extraction methods fail for these object types. The new developed algorithm is presented and realized}, language = {en} } @inproceedings{ChizhovaGurianovBrunnetal., author = {Chizhova, Maria and Gurianov, Andrey and Brunn, Ansgar and Stilla, Uwe and Luhmann, Thomas}, title = {Wavelet-basierte Erkennung architektonischer Formen aus pr{\"a}zisen Punktwolken}, series = {Beitr{\"a}ge der Oldenburger 3D-Tage 2017}, booktitle = {Beitr{\"a}ge der Oldenburger 3D-Tage 2017}, editor = {Luhmann, Thomas and Schumacher, C.}, publisher = {Wichmann-Verlag}, address = {Berlin}, pages = {129 -- 141}, language = {de} } @inproceedings{ChizhovaKorovinBrunnetal., author = {Chizhova, M. and Korovin, D. and Brunn, Ansgar and Stilla, Uwe}, title = {Automatical Segmentation of Cupola Blocks from Unorganized Point Clouds}, series = {Proceedings of the GEOSPACE Congress 2016, Kiew}, booktitle = {Proceedings of the GEOSPACE Congress 2016, Kiew}, language = {en} } @article{MeyerBrunnStilla, author = {Meyer, Theresa and Brunn, Ansgar and Stilla, Uwe}, title = {Change detection for indoor construction progress monitoring based on BIM, point clouds and uncertainties}, series = {Automation in Construction}, volume = {141}, journal = {Automation in Construction}, issn = {0926-5805}, doi = {doi.org/10.1016/j.autcon.2022.104442}, abstract = {Automatic construction progress documentation and metric evaluation of execution work in confined building interiors requires particularly reliable geometric evaluation and interpretation of statistically uncertain as-built point clouds. This paper presents a method for high-resolution change detection based on dense 3D point clouds from terrestrial laser scanning (TLS) and the discretization of space by voxels. In order to evaluate the metric accuracy of a BIM according to the Level of Accuracy (LOA) specification, the effects of laser range measurements on the occupancy of space are modeled with belief functions and evaluated using Dempster and Shafer's theory of evidence. The application is demonstrated on the point cloud data of multi temporal scanning campaigns of real indoor reconstructions. The results show that TLS point clouds are suitable to verify a given BIM up to LOA 40 if special attention is paid to the scanning geometry during the acquisition. The proposed method can be used to document construction progress, verify and even update the LOA status of a given BIM, confirming valid and BIM-compliant as-built models for further planning.}, language = {en} } @article{MeyerBrunnStilla, author = {Meyer, Theresa and Brunn, Ansgar and Stilla, Uwe}, title = {Geometric BIM verification of indoor construction sites by photogrammetric point clouds and evidence theory}, series = {ISPRS Journal of Photogrammetry and Remote Sensing}, volume = {195}, journal = {ISPRS Journal of Photogrammetry and Remote Sensing}, pages = {432 -- 445}, abstract = {Photogrammetric point clouds offer immense potential for various applications, especially for the AEC industry and "as-built" BIM. However, despite many advantages such as time and cost efficiency, image based point clouds of indoor environments mostly suffer from inhomogeneous and strongly fluctuating point-wise uncertainties. This lack of area-filling geometric reliability represents a strong barrier for innovations and further development of image based applications for as-built BIM, regarding both software and hardware. Therefore, this paper presents a method for the geometric verification of indoor BIMs by images and uncertainty management in order to unleash the potential of photogrammetry in context of professional building documentation heading towards "digital twinning". Individual 3D point accuracies, object's surface characteristics and BIM related uncertainties according to the Level of Accuracy (LOA) specification are assessed and taken into account. The final decision of whether or not a photogrammetric point cloud confirms a given model within its associated level of accuracy results from a combined reasoning pipeline based on Dempster-Shafer evidence theory. The novel Pho-to-BIM verification method is demonstrated on three real indoor construction sites, each 3D mapped with different image sensors. Based on the experiments it is shown how to set up belief functions for evidence based reasoning individually, depending on the measurement and site characteristics.}, language = {en} } @article{BrodovskiiKorovinChizhovaetal., author = {Brodovskii, Maksim and Korovin, Dmitrii and Chizhova, Maria and Brunn, Ansgar and Stilla, Uwe}, title = {Recognizing Separate Structural Elements of Churches Using Neural Network}, series = {Dreil{\"a}ndertagung der DGPF, der OVG und der SGPF in Bern, Schweiz - Publikationen der DGPF}, journal = {Dreil{\"a}ndertagung der DGPF, der OVG und der SGPF in Bern, Schweiz - Publikationen der DGPF}, abstract = {In this paper we develop a new approach to recognize structural elements of orthodox churches. We will work with 3D point clouds, received as a result of 3D point cloud acquisitions of churches, e.g. from laser scanning. Because of the large amount of points in such clouds, we have to use a projection (elevation) to decrease the calculation effort. To get meaningful images from the projection of the point cloud we do some prior segmentation of the 3D cloud. Images binary, with a predefined resolution that depends on the resolution of the 3D point cloud. To recognize elements we decide to use neural networks (Perceptron and Counter propagation neural networks) as they allow the automation of the process and have a broad range of methods to recognize images. For the subsequent 3D modeling we use analytic expressions, that describe each of the structural church elements. A further step is the deduction of those expressions that describe each of the recognized sectional views}, language = {en} } @article{MeyerBrunnStilla, author = {Meyer, Theresa and Brunn, Ansgar and Stilla, Uwe}, title = {Accuracy investigation on image-based change detection for BIM compliant indoor models}, series = {ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, volume = {4}, journal = {ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, pages = {105 -- 112}, language = {en} }