Component Identification and Interpretation

3D modeling of buildings is an important method in mapping and modeling the built environment. In this study, we analyzed the differences between the semantic state of actual buildings and 3D models of LoD3 buildings generated using aerial and terrestrial photogrammetric methods. We also evaluated the accuracy of the visual representation as well as the suitability of the building geometry and texture. Our method involves collecting aerial and terrestrial photographic data and processing it using SFM (structure from motion) technology. The photogrammetric data was then processed using image matching algorithms and 3D reconstruction techniques to generate 3D models of LoD3 buildings. The actual semantic state of the building was identified through field surveys and reference data collection. The 3D building model was successfully modeled from 1201 photos and 19 ground control points. The results of the evaluation of the geometry accuracy test, dimensions and semantic completeness of the 3D model, the use of aerial photographs and terrestrial photogrammetry in LoD3 3D modeling are assessed from the results of the automatic 3D modeling process using SfM (Structure from Motion) technology that produces 3D building models in Level of Detail (LoD) 3 with Root Mean Square Error values <0.5 meters and has semantic completeness of the building in accordance with the original object based on the City Geography Markup Language (CityGML) standard. The facade formed from the modeling almost follows the original model such as doors, windows, hallways, etc.

PurposeThe current technique used to measure construction is the conventional total station method. However, the conventional method is time-consuming and could not be used to create a photo-realistic three-dimensional (3D) model of an object. Furthermore, the Canseleri building is located at a slope. The paper aims to discuss this issue.Design/methodology/approachThe aim of this study is to assess the geometric accuracy of a 3D model using unmanned aerial vehicle (UAV) images. There are two objectives in this study. The first is to construct a 3D model of the Canseleri building using UAV images. The second objective is to validate the 3D model of the Canseleri building based on actual measurements.FindingsThe close-range photogrammetry method, using the UAV platform, was able to produce a 3D building model. The results show that the errors between the actual measurement and the generated 3D model were less than 4 cm. The accuracy of the 3D model achieved in this study was about 0.015 m, compared to total station measurements.Originality/valueAccuracy assessment was done by comparing the estimated measurement of the 3D model with the direct measurement. The differences between the measured values with actual values could be compared. Based on this study, the 3D building model gave a reliable accuracy for specific applications.

Abstract. With recent government initiatives for smart cities, 3D virtual city models are in demand for managing and monitoring the urban infrastructure. 3D building models forms an important component of 3D virtual city model. LiDAR remote sensing has revolutionized the way the third dimension can be precisely mapped and proved to be an important source of data for 3D models. The model thus generated should be in an open data format to be used across various applications. CityGML is an open data model framework that enables storage and exchange of 3D models which can be used for diversified applications. The main objective of this research is to develop a methodological workflow to create 3D building models in CityGML standard from airborne LiDAR point cloud. Initially building points were isolated from the airborne LiDAR data using point cloud processing algorithms. 3D building models with levels of detail (LoD1 and LoD2) were generated from the building points in CityGML standard using commercial (ArcGISPro) well as open source packages (3dfier, Citygml4j). Results prove that the models developed using open source packages are comparable to that provided by commercial packages.

Abstract. Photo-realistic 3D model of object cannot be created by using conventional Total Station method. The aim of this study is to generate 3D building model using UAV’s dense point clouds. In this research, the ability of remotely detected information for the construction of 3D building models is found to be as specific as UAV datasets, Tacheometry Survey and Traverse Survey. Pix4D and MeshLab software were used in this study to perform image processing of 3D building. The building was built up upon using the information needed from capturing UAV images. This procedure requires the height of building to be measured through conventional method such that of UAV and the height is then compared with a 3D building model. At the end of the process, the comparison of height of building, also known as RMSE, was conducted. The images of building were then processed in Photogrammetry which is the Pix4D software. Using Pix4D, this study proceeded with several processing stages such as camera calibration, photo uploading, building of dense cloud, mesh generation, and model texturing. Those processes were done automatically by using Pix4D tools. High quality of photo-realistic 3D model of building was then successfully constructed. The accuracy assessment was done by comparing the measurement of 3D model of building. Direct measuring of building by using total station had taken place to compare the measurements between 3D model details with actual measurements. The measurement of 3D model of building was done in Pix4D software. The RMSE achieved in this study is 0.015 m which is under reasonable accuracy limit. This study proves that UAV point cloud is capable to produce a very fine 3D model.

Abstract. 3D city models are increasingly being used to represent the complexity of today’s urban areas, as they aid in understanding how different aspects of a city can function. For instance, several municipalities and governmental organisations have constructed their 3D city models for various purposes. These 3D models, which are normally complex and contain semantics information, have typically been used for visualisation and visual analysis purposes. However, most of the available 3D models open datasets contain many geometric and topological errors, e.g., missing surfaces (holes), self-intersecting surfaces, duplicate vertices, etc. These errors prevent the datasets from being used for advanced applications such as 3D spatial analysis which requires valid datasets and topology to calculate its volume, detect surface orientation, area calculation, etc. Therefore, certain repairs must be done before taking these models into actual applications, and hole-filling (of missing surfaces) is an important one among them. Several studies on the topic of automatic repair of the 3D model have been conducted by various researchers, with different approaches have been developed. Thus, this paper describes a triangular mesh approach for automatically repair invalid (missing surfaces) 3D building model (LOD2). The developed approach demonstrates an ability to repair missing surfaces (with holes) in a 3D building model by reconstructing geometries of the holes of the affected model. The repaired model is validated and produced a closed-two manifold model.

Nowadays, 3D city models are used by the increasing number of applications. Most applications require not only geometric information but also semantic information. As a standard and tool for 3D city model, CityGML, provides a method for storing and managing both geometric and semantic information. Moreover, it also provides the multi-scale representation of 3D building model for efficient visualization. In CityGML, building models are represented in five LODs (Level of Detail), start from LOD0, LOD1, LOD2, LOD3, and LOD4. Each level has different accuracy and detail requirement for visualization. Usually, for obtaining multi-LOD of 3D building model, several data sources are integrated. For example, LiDAR data is used for generating LOD0, LOD1, and LOD2 as close-range photogrammetry data is used for generating more detailed model in LOD3 and LOD4. However, using additional data sources is increasing cost and time consuming. Since the development of TLS (Terrestrial Laser Scanner), data collection for detailed model can be conducted in a relative short time compared to photogrammetry. Point cloud generated from TLS can be used for generating the multi-LOD of building model. This paper gives an overview about the representation of 3D building model in CityGML and also method for generating multi-LOD of building from TLS data. An experiment was conducted using TLS. Following the standard in CityGML, point clouds from TLS were processed resulting 3D model of building in different level of details. Afterward, models in different LOD were converted into XML schema to be used in CityGML. From the experiment, final result shows that TLS can be used for generating 3D models of building in LOD1, LOD2, and LOD3.

This paper proposes a method of generating 3D building models with precise geospatial information and a photograph-based facade appearance from panoramic image sequences and digital maps. 3D building modeling research is actively being conducted in areas such as geographic information systems, virtual reality, and augmented reality. However, the generation of realistic 3D models from a ground-level viewpoint is still extremely costly in terms of labor of modeling experts, and collection of data. We have developed a method for 3D building modeling with high-resolution photograph-based appearance information using panoramic images captured at ground level with a mobile mapping system, and geospatial information obtained from a digital map. The proposed method includes 1) pre-processing for tilt correction and base 3D model generation, 2) geo-registration of panoramic images with minimal user input, and 3) building height and shape estimation. This paper presents the proposed method and the quantitative performance measure obtained from a developed test modeling system. In addition, modeling results from an experimental dataset are also presented.

Interoperability and data exchange within BIM platform to evaluate building energy performance and indoor comfort

Use of MCAM in creating 3D neutronics model for ITER building

3-Dimensional (3D) Building Information Model (BIM) can help students’ learning in Construction Management (CM) courses. 3D models can help students visualize the information from plans in format of 2D into 3D. Due to this benefit, 3D models have been used in diverse CM courses, and the effectiveness of 3D models in diverse CM courses have been proven to be positive. However, the usage of 3D models in estimating courses has not been clearly proven by existing literatures. Furthermore, accurate estimating requires multiple estimating tasks starting with visualizing building components. There is no existing study on how effective the usage of 3D models is for each of the estimating sub-tasks. This study aimed to explore effectiveness of 3D models in estimating related tasks through students’ perception on effectiveness of 3D models in an estimating course at a 4-year college in the U.S. The results of this study show that overall, the 3D models were effective in all the estimating tasks. Also, ‘visualizing building components’, ‘locating building components’, and ‘identifying building components' are the estimating sub-tasks in which the 3D models were the most effective.

Processing existing building geometry for reuse as Linked Data

The applications of 3D building models are limited as producing them requires massive labor and time costs as well as expensive devices. In this paper, we aim to propose a novel and web-based interactive platform, VGI3D, to overcome these challenges. The platform is designed to reconstruct 3D building models by using free images from internet users or volunteered geographic information (VGI) platform, even though not all these images are of high quality. Our interactive platform can effectively obtain each 3D building model from images in 30 seconds, with the help of user interaction module and convolutional neural network (CNN). The user interaction module provides the boundary of building facades for 3D building modeling. And this CNN can detect facade elements even though multiple architectural styles and complex scenes are within the images. Moreover, user interaction module is designed as simple as possible to make it easier to use for both of expert and non-expert users. Meanwhile, we conducted a usability testing and collected feedback from participants to better optimize platform and user experience. In general, the usage of VGI data reduces labor and device costs, and CNN simplifies the process of elements extraction in 3D building modeling. Hence, our proposed platform offers a promising solution to the 3D modeling community.

This paper presents a data-driven free-form modelling method dedicated to the parametric modelling of buildings with complex shapes located in particularly valuable Old Town Centres, using Airborne LiDAR Scanning (ALS) data and aerial imagery. The method aims to reconstruct and preserve the input point cloud based on the relative density of the data. The method is based on geometric operations, iterative transformations between point clouds, meshes, and shape identification. The method was applied on a few buildings located in the Old Town Centre of Bordeaux (France). The 3D model produced shows a mean distance to the point cloud of 0.058 m and a standard deviation of 0.664 m. In addition, the incidence of building footprint segmentation techniques in automatic and interactive model-driven modelling was investigated and, in order to identify the best approach, six different segmentation methods were tested. The segmentation was performed based on the footprints derived from Digital Surface Model (DSM), point cloud, nadir images, and OpenStreetMap (OSM). The comparison between the models shows that the segmentation that produces the most accurate and precise model is the interactive segmentation based on nadir images. This research also shows that in modelling complex structures, the model-driven method can achieve high levels of accuracy by including an interactive editing phase in building 3D models.

The essential techniques used in 3D model reconstruction are LIDAR scanning, close-range photogrammetry, and aerial photogrammetry. The aim of this study is to investigate 3D building model results using a UAV platform using different altitudes and ranges. The methodology was divided into four phases. Phase one was a preliminary study and phase two was the data acquisition phase which included flight planning, camera calibration, and image acquisition at three different altitudes; 150m, 170m, and 190m and at different ranges; 180m, 190m, and 200m, respectively. Phase three was data processing whereby the resulting 3D models were generated using five steps which are image masking, image aligning, image dense clouding, image meshing, and image texturing. Phase four contained analyses on the 3D model such as accuracy assessment of the 3D model and analysis on the different altitudes and ranges employed. This study stated that the maximum accuracy was 0.195m without a control point, while the minimum accuracy was 0.123m with a control point. It shows that the 3D model with a control point produced measurements that were 37% more accurate than the 3D model without a control point. In the final analysis, the results showed that the built 3D model resulting from the UAV platform can provide an accuracy of less than 0.200m with or without control points. These findings can be applied to many fields, such as heritage and conservation in the efforts to preserve the 3D model of heritage objects.

Accurate three-dimensional (3D) models for Heritage Building Information Modeling (HBIM) remain a significant challenge. This paper proposes a methodology that combines the Poisson Surface Reconstruction (PSR) technique with open-source management software to address this issue. The methodology uses automatically generated mesh models to produce reality-based 3D models of historical buildings. These models are enriched with geometric and semantic parameters according to BIM standards. The resulting methodology, Scan to MesHBIM, is an open 3D interface allowing experts to analyze and create a detailed set of properties adhering to construction rules. To test the workflow, we selected two case studies of different vaulting types: the Renaissance barrel vault with cloister heads and lunettes from the Ducal Palace in Urbino (Italy) and the Gothic ribbed vault from St. André Cathedral in Bourdeaux (France). The use of implicit surfaces proved to be an efficient means for obtaining accurate 3D objects; then, the enrichment of the 3D models ensures a better understanding and more in-depth management in the field of Cultural Heritage (CH).