References of "Billen, Roland"
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See detailA Built Heritage Information System Based on Point Cloud Data: HIS-PC
Poux, Florent ULiege; Billen, Roland ULiege; Kasprzyk, Jean-Paul ULiege et al

in ISPRS International Journal of Geo-Information (2020), 9(10), 588

The digital management of an archaeological site requires to store, organise, access and represent all the information that is collected on the field. Heritage building information modelling ... [more ▼]

The digital management of an archaeological site requires to store, organise, access and represent all the information that is collected on the field. Heritage building information modelling, archaeological or heritage information systems now tend to propose a common framework where all the materials are managed from a central database and visualised through a 3D representation. In this research, we offer the development of a built heritage information system prototype based on a high-resolution 3D point cloud data set. The particularity of the approach is to consider a user-centred development methodology while avoiding meshing/down-sampling operations. The proposed system is initiated by a close collaboration between multi-modal users (managers, visitors, curators) and a development team (designers, developers, architects). The developed heritage information system permits the management of spatial and temporal information, including a wide range of semantics using relational along with NoSQL databases. The semantics used to describe the artifacts are subject to conceptual modelling. Finally, the system proposes a bi-directional communication with a 3D interface able to stream massive point clouds, which is a big step forward to provide a comprehensive site representation for stakeholders while minimising modelling costs. [less ▲]

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See detailNew 3D standards and perspectives
Nys, Gilles-Antoine ULiege; Billen, Roland ULiege

Scientific conference (2020, September 22)

Presentation of the last developments of the 3D Standard of the OGC Family: CityGML 3.0 and CityJSON.

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See detail3D Viewpoint Optimization of Topological Relationships: Application to 3D Cadastre for Visual Easement Validation
Neuville, Romain ULiege; Jacynthe, Pouliot; Billen, Roland ULiege

in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2020, September 03), VI-4/W1-2020

Offering optimum 3D viewpoint to user can be attractive in relieving occlusion in 3D scene. This could be much relevant for the visualization of 3D cadastral systems since they constitute complex datasets ... [more ▼]

Offering optimum 3D viewpoint to user can be attractive in relieving occlusion in 3D scene. This could be much relevant for the visualization of 3D cadastral systems since they constitute complex datasets including both physical and legal objects while users are operating a number of visual tasks that require precise outlook. However, 3D viewpoint usability has yet to be evaluated to demonstrate its relevance in accomplishing given end user’s visual tasks. Hence, in this research project, the focus is set on visual identification of 3D topological relationships (disjoint and overlap) as it is one of the main users’ requirements in 3D cadastre. To this end, this paper addresses this issue using a virtual 3D model of the Planetarium Rio Tinto Alcan (Montreal city) in which property issues take place, especially regarding the easement validation procedure. Empirical tests have then been administrated in the form of interviews using an online questionnaire with university students who will specifically address such issues in their professional career. The results show that a 3D viewpoint that maximizes 3D disjoined or overlapped geometric objects’ view area within the viewport significantly outperforms traditional combined software points of view in visually identifying 3D topological relationship. This paper also suggests that user’s inexperience in 3D cadastre reduces visual task efficiency when visually identifying 3D topological relationship among overlapped geometric objects. Eventually, this study opens up new perspectives on 3D topological relationships modeling and visualization. [less ▲]

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See detailCityJSON Building Generation from Airborne LiDAR 3D Point Clouds
Nys, Gilles-Antoine ULiege; Poux, Florent ULiege; Billen, Roland ULiege

in ISPRS International Journal of Geo-Information (2020), 9(521),

The relevant insights provided by 3D City models greatly improve Smart Cities and their management policies. In the urban built environment, buildings frequently represent the most studied and modeled ... [more ▼]

The relevant insights provided by 3D City models greatly improve Smart Cities and their management policies. In the urban built environment, buildings frequently represent the most studied and modeled features. CityJSON format proposes a lightweight and developer-friendly alternative to CityGML. This paper proposes an improvement to the usability of 3D models providing an automatic generation method in CityJSON, to ensure compactness, expressivity, and interoperability. In addition to a compliance rate in excess of 92% for geometry and topology, the generated model allows the handling of contextual information, such as metadata and refined levels of details (LoD), in a built-in manner. By breaking down the building-generation process, it creates consistent building objects from the unique source of Light Detection and Ranging (LiDAR) point clouds. [less ▲]

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See detailMARKER-LESS MOBILE AUGMENTED REALITY APPLICATION FOR MASSIVE 3D POINT CLOUDS AND SEMANTICS
Kharroubi, Abderrazzaq ULiege; Billen, Roland ULiege; Poux, Florent ULiege

in International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2020, August 12), XLIII(B2), 255261

Mobile Augmented Reality (MAR) attracts significant research and development efforts from both the industry and academia, but rarely integrate massive 3D dataset’s interactions. The emergence of dedicated ... [more ▼]

Mobile Augmented Reality (MAR) attracts significant research and development efforts from both the industry and academia, but rarely integrate massive 3D dataset’s interactions. The emergence of dedicated AR devices and powerful Software Development Kit (ARCore for android and ARKit for iOS) improves performance on mobile devices (Smartphones and tablets). This is aided by new sensor integration and advances in computer vision that fuels the development of MAR. In this paper, we propose a direct integration of massive 3D point clouds with semantics in a web-based marker-less mobile Augmented Reality (AR) application for real-time visualization. We specifically investigate challenges linked to point cloud data structure and semantic injection. Our solution consolidates some of the overarching principles of AR, of which pose estimation, registration and 3D tracking. The developed AR system is tested on mobile phones web-browsers providing clear insights on the performance of the system. Promising results highlight a number of frame per second varying between 27 and 60 for a real-time point budget of 4.3 million points. The point cloud tested is composed of 29 million points and shows how our indexation strategy permits the integration of massive point clouds aiming at the point budget. The results also gives research directions concerning the dependence and delay related to the quality of the network connection, and the battery consumption since portable sensors are used all the time. [less ▲]

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See detailAutomatic 3D Buildings Compact Reconstruction from LiDAR point clouds
Nys, Gilles-Antoine ULiege; Billen, Roland ULiege; Poux, Florent ULiege

in International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2020, August 12), (XLIII-B2-2020), 473-478

Point clouds generated from aerial LiDAR and photogrammetric techniques are great ways to obtain valuable spatial insights over large scale. However, their nature hinders the direct extraction and sharing ... [more ▼]

Point clouds generated from aerial LiDAR and photogrammetric techniques are great ways to obtain valuable spatial insights over large scale. However, their nature hinders the direct extraction and sharing of underlying information. The generation of consistent large-scale 3D city models from this real-world data is a major challenge. Specifically, the integration in workflows usable by decision-making scenarios demands that the data is structured, rich and exchangeable. CityGML permits new advances in terms of interoperable endeavour to use city models in a collaborative way. Efforts have led to render good-looking digital twins of cities but few of them take into account their potential use in finite elements simulations (wind, floods, heat radiation model, etc.). In this paper, we target the automatic reconstruction of consistent 3D city buildings highlighting closed solids, coherent surface junctions, perfect snapping of vertices, etc. It specifically investigates the topological and geometrical consistency of generated models from aerial LiDAR point cloud, formatted following the CityJSON specifications. These models are then usable to store relevant information and provides geometries usable within complex computations such as computational fluid dynamics, free of local inconsistencies (e.g. holes and unclosed solids). [less ▲]

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See detailInitial User-Centered Design of a Virtual Reality Heritage System: Applications for Digital Tourism
Poux, Florent ULiege; Valembois, Quentin ULiege; Mattes, Christian et al

in Remote Sensing (2020), 12(16), 2583

Reality capture allows for the reconstruction, with a high accuracy, of the physical reality of cultural heritage sites. Obtained 3D models are often used for various applications such as promotional ... [more ▼]

Reality capture allows for the reconstruction, with a high accuracy, of the physical reality of cultural heritage sites. Obtained 3D models are often used for various applications such as promotional content creation, virtual tours, and immersive experiences. In this paper, we study new ways to interact with these high-quality 3D reconstructions in a real-world scenario. We propose a user-centric product design to create a virtual reality (VR) application specifically intended for multi-modal purposes. It is applied to the castle of Jehay (Belgium), which is under renovation, to permit multi-user digital immersive experiences. The article proposes a high-level view of multi-disciplinary processes, from a needs analysis to the 3D reality capture workflow and the creation of a VR environment incorporated into an immersive application. We provide several relevant VR parameters for the scene optimization, the locomotion system, and the multi-user environment definition that were tested in a heritage tourism context [less ▲]

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See detailTowards a CityGML 3D Property Valuation Model based on BIM
El Yamani, Siham ULiege; Billen, Roland ULiege; Hajji, Rafika

Conference (2020, July 02)

3D variables have a substantial influence on the property value. In the same building, property units are exposed differently to environmental conditions, such as: sunlight exposure, air quality etc. and ... [more ▼]

3D variables have a substantial influence on the property value. In the same building, property units are exposed differently to environmental conditions, such as: sunlight exposure, air quality etc. and each unit is made up of a variety and complex attributes (materials, cost, energy efficiency etc.). These parameters are some of the main 3D variables impacting the property value. Therefore, a number of studies has been carried out recently to introduce 3D modeling techniques and 3D data sources in order to improve the assessment of property units’ value. These studies include the recent achievement regarding the International Valuation Information Model, an extension of the ISO 19152:2012 Land Administration Domain Model (LADM). It is developed for immovable property taxation to serve valuation practices in administration authorities. It provides also information related to physical property units’ characteristics, locational and some environmental characteristics. The physical variables are mainly derived from the 3D cadastral model while 3D locational and environmental variables are derived from 3D spatial datasets. These variables are integrated into the LADM-Valuation Information Model. However, this model approaches the property valuation on a 3D cadastral and 3D legal viewpoint, we choose to address the problem in a different perspective, considering that a property value can be defined by its indoors variables Building Information Model (BIM) and outdoors variables specified from the CityGML 3D geospatial standard. To tackle this approach, the first outline of our research is to examine how to select the significant 3D variables for property valuation and to identify the relevant 3D data sources required to construct the property valuation model for the indoors (BIM) and outdoors (CityGML). The expected outcome of this research is to develop a generic property valuation model to support real estate valuers, contractors, developers and administrations. The proposed approach can be meaningful to the existing International Valuation Information Model. It may be considered for the future investigation for integrating 3D variables that impact property valuation. [less ▲]

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See detailThe Coudenberg Heritage Building Information System
Billen, Roland ULiege

Conference (2020, June 18)

Detailed reference viewed: 36 (4 ULiège)
See detailMéthodes de levé des cours d'eau canalisés
Billen, Roland ULiege

Conference given outside the academic context (2019)

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See detailCLASSIFICATION AND INTEGRATION OF MASSIVE 3D POINTS CLOUDS IN A VIRTUAL REALITY (VR) ENVIRONMENT
Kharroubi, Abderrazzaq ULiege; Hajji, Rafika; Billen, Roland ULiege et al

in International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2019, November 29), XLII-2(W17), 165-171

With the increasing volume of 3D applications using immersive technologies such as virtual, augmented and mixed reality, it is very interesting to create better ways to integrate unstructured 3D data such ... [more ▼]

With the increasing volume of 3D applications using immersive technologies such as virtual, augmented and mixed reality, it is very interesting to create better ways to integrate unstructured 3D data such as point clouds as a source of data. Indeed, this can lead to an efficient workflow from 3D capture to 3D immersive environment creation without the need to derive 3D model, and lengthy optimization pipelines. In this paper, the main focus is on the direct classification and integration of massive 3D point clouds in a virtual reality (VR) environment. The emphasis is put on leveraging open-source frameworks for an easy replication of the findings. First, we develop a semi-automatic segmentation approach to provide semantic descriptors (mainly classes) to groups of points. We then build an octree data structure leveraged through out-of-core algorithms to load in real time and continuously only the points that are in the VR user's field of view. Then, we provide an open-source solution using Unity with a user interface for VR point cloud interaction and visualisation. Finally, we provide a full semantic VR data integration enhanced through developed shaders for future spatio-semantic queries. We tested our approach on several datasets of which a point cloud composed of 2.3 billion points, representing the heritage site of the castle of Jehay (Belgium). The results underline the efficiency and performance of the solution for visualizing classifieds massive point clouds in virtual environments with more than 100 frame per second. [less ▲]

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See detailSemantic enrichment of point cloud by automatic extraction and enhancement of 360° panoramas
Tabkha, A.; Hajji, R.; Billen, Roland ULiege et al

in International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2019, November 29), XLII-2(W17), 355-362

The raw nature of point clouds is an important challenge for their direct exploitation in architecture, engineering and construction applications. Particularly, their lack of semantics hinders their ... [more ▼]

The raw nature of point clouds is an important challenge for their direct exploitation in architecture, engineering and construction applications. Particularly, their lack of semantics hinders their utility for automatic workflows (Poux, 2019). In addition, the volume and the irregularity of the structure of point clouds makes it difficult to directly and automatically classify datasets efficiently, especially when compared to the state-of-the art 2D raster classification. Recently, with the advances in deep learning models such as convolutional neural networks (CNNs) , the performance of image-based classification of remote sensing scenes has improved considerably (Chen et al., 2018; Cheng et al., 2017). In this research, we examine a simple and innovative approach that represent large 3D point clouds through multiple 2D projections to leverage learning approaches based on 2D images. In other words, the approach in this study proposes an automatic process for extracting 360° panoramas, enhancing these to be able to leverage raster data to obtain domain-base semantic enrichment possibilities. Indeed, it is very important to obtain a rigorous characterization for use in the classification of a point cloud. Especially because there is a very large variety of 3D point cloud domain applications. In order to test the adequacy of the method and its potential for generalization, several tests were performed on different datasets. The developed semantic augmentation algorithm uses only the attributes X, Y, Z and camera positions as inputs. [less ▲]

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See detailLe numérique au Château de Jehay
Billen, Roland ULiege

Conference given outside the academic context (2019)

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See detailIntegration of multiple sensor data into a 3D GIS for cities monitoring
Kasprzyk, Jean-Paul ULiege; Nys, Gilles-Antoine ULiege; Billen, Roland ULiege

Conference (2019, October 18)

This research is part of a larger project, called “Ecocity Tools”, which aims to establish environment and energy diagnostics for cities at the neighborhood scale. Experts in different fields provide ... [more ▼]

This research is part of a larger project, called “Ecocity Tools”, which aims to establish environment and energy diagnostics for cities at the neighborhood scale. Experts in different fields provide information based on both scientific models (climatology, pollutant dispersions) and sensor data (energetic cadaster, air quality) to a 3D GIS for decision support in urban planning. This paper focuses on two interconnected problematics about the use of GIS in a “Smart City” approach: an appropriate 3D geometric model and the integration of sensor data into this model. As buildings can be equipped by several sensors in multiples locations (rooms, floors, walls, etc), information should be attachable to specific geometric parts (like walls). It is thus important for 3D city models to be adapted to detailed scale levels. Thanks to the consideration of different levels of details (LoD), from buildings footprints (LoD 0) to interiors (LoD 4), the CityGML standard (OGC) can theoretically fit any 3D application. Nevertheless, these data are not always available at very detailed levels. For example, Belgian authorities deliver open data in CityGML LoD 2 (representing buildings as volumes with simplified roof shapes) for important cities like Brussels or Namur. Therefore, this paper proposes a PostGIS data model able to attach information to specific building parts even in poorly detailed city models (LoD 1 or 2). The second part of this research is the implementation of other OGC standards specifically for the visualization of sensor data into a GIS: Sensor Observation Service (SOS) and SensorThings API (STA). As Web Feature Service (WFS) does for geographical features, SOS allows any compatible GIS client to import georeferenced sensor data and metadata through a simple http request (including filters on space, time and other attributes). More recently, STA, in addition to SOS functions, supports JSON format for data exchanges and also provides a “Tasking Part”: the STA server is able to ask sensors and actuators to do specific tasks like “start/stop measurements”. In this research, a SOS server, able to communicate with the 3D GIS, is implemented thanks to the open source tool provided by 52North. [less ▲]

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See detailSmart point clouds : Les dernières avancées en termes de structuration des nuages de points.
Poux, Florent ULiege; Billen, Roland ULiege

Conference given outside the academic context (2019)

Detailed reference viewed: 48 (3 ULiège)
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See detailA Smart Point Cloud Infrastructure for intelligent environments
Poux, Florent ULiege; Billen, Roland ULiege

in Lindenbergh, Roderik; Riveiro-Rodríguez, Belén (Eds.) Laser scanning: an emerging technology in structural engineering (2019)

3D point cloud data describes our physical world spatially. Knowledge discovery processes including semantic segmentation and classification are a great way to complement this information by leveraging ... [more ▼]

3D point cloud data describes our physical world spatially. Knowledge discovery processes including semantic segmentation and classification are a great way to complement this information by leveraging analytic or domain knowledge to extract semantics. Combining efficiently this information is an opening on intelligent environments and deep automation. This chapter provides a conceptual data model to structure 3D point data, semantics and topology proficiently. It aims at creating an interactive clone of the real world usable by cognitive decision systems. A multi-modal infrastructure integrating this data model is presented that includes knowledge extraction, knowledge integration and knowledge representation for automatic agent-based decision-making over enriched point cloud data. A knowledge base processing with ontologies is provided for extended interoperability. [less ▲]

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See detailIdentification of the Best 3D Viewpoint within the BIM Model: Application to Visual Tasks Related to Facility Management
Neuville, Romain ULiege; Pouliot, Jacynthe; Billen, Roland ULiege

in Buildings (2019), 9(7), 167

Visualizing building assets within building information modeling (BIM) offers significant opportunities in facility management as it can assist the maintenance and the safety of buildings. Nevertheless ... [more ▼]

Visualizing building assets within building information modeling (BIM) offers significant opportunities in facility management as it can assist the maintenance and the safety of buildings. Nevertheless, taking decisions based on 3D visualization remains a challenge since the high density of spatial information inside the 3D model requires suitable visualization techniques to achieve the visual task. The occlusion is ubiquitous and, whilst solutions already exist such as transparency, none currently solve this issue with an automatic and suitable management of the camera. In this paper, we propose the first RESTful web application implementing a 3D viewpoint management algorithm and we demonstrate its usability in the visualization of assets based on a BIM model for visual counting in facility management. Via an online questionnaire, empirical tests are conducted with architects, the construction industry, engineers, and surveyors. The results show that a 3D viewpoint that maximizes the visibility of 3D geometric objects inside the viewport significantly improves the success rate, the accuracy, and the certainty of a visual counting task compared to the traditional four side points of view (i.e., from the front, back, left, and right viewpoints). Finally, this first validation lays the foundation of future investigations in the 3D viewpoint usability evaluation, both in terms of visual tasks and application domains. [less ▲]

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See detailA Semantic Retrieval System for Remote Sensing Web Platforms
Nys, Gilles-Antoine ULiege; Kasprzyk, Jean-Paul ULiege; Hallot, Pierre ULiege et al

Conference (2019, June 13)

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See detailA Semantic Retrieval System for Remote Sensing Web Platforms
Nys, Gilles-Antoine ULiege; Kasprzyk, Jean-Paul ULiege; Hallot, Pierre ULiege et al

in International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2019, June 05), XLII-2(W13), 1593-1599

This paper proposes a solution to reduce the semantic gap between final users and data/processing providers in a web market place dedicated to remote sensing products. Nowadays, search engine are common ... [more ▼]

This paper proposes a solution to reduce the semantic gap between final users and data/processing providers in a web market place dedicated to remote sensing products. Nowadays, search engine are common tools on the Internet. Users are accustomed to use them and used to get tabular classification of provided answers. These smart agents are set up to answer basic questions using automatic pages redirection or chitchat. In this research, to ensure coherence between user’s requests and platform answers, natural language processing algorithms and knowledge graphs are integrated within a web platform thanks to a NoSQL graph database connected to open thesauri and Geographic Information Systems (GIS). Therefore, the most pertinent services can be proposed based on input sentences including non-technical vocabulary but also geographical components (the user interface includes a text area and an interactive map). While processing chains and remote sensing ontologies were presented in one of our previous studies, this article focuses on natural languages algorithms and knowledge mining. [less ▲]

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See detailVoxel-Based 3D Point Cloud Semantic Segmentation: Unsupervised Geometric and Relationship Featuring vs Deep Learning Methods
Poux, Florent ULiege; Billen, Roland ULiege

in ISPRS International Journal of Geo-Information (2019), 8(5), 213

Automation in point cloud data processing is central in knowledge discovery within decision-making systems. The definition of relevant features is often key for segmentation and classification, with ... [more ▼]

Automation in point cloud data processing is central in knowledge discovery within decision-making systems. The definition of relevant features is often key for segmentation and classification, with automated workflows presenting the main challenges. In this paper, we propose a voxel-based feature engineering that better characterize point clusters and provide strong support to supervised or unsupervised classification. We provide different feature generalization levels to permit interoperable frameworks. First, we recommend a shape-based feature set (SF1) that only leverages the raw X, Y, Z attributes of any point cloud. Afterwards, we derive relationship and topology between voxel entities to obtain a three-dimensional (3D) structural connectivity feature set (SF2). Finally, we provide a knowledge-based decision tree to permit infrastructure-related classification. We study SF1/SF2 synergy on a new semantic segmentation framework for the constitution of a higher semantic representation of point clouds in relevant clusters. Finally, we benchmark the approach against novel and best-performing deep-learning methods while using the full S3DIS dataset. We highlight good performances, easy-integration, and high F1-score (> 85%) for planar-dominant classes that are comparable to state-of-the-art deep learning. [less ▲]

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