• Spatial Information Research
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• v.22 no.6
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• pp.33-43
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• 2014

As the number of people who live indoor space has been increased, the interest in 3D indoor spatial information has been grown. Object-Oriented 3D indoor space modeling including indoor spatial information has performed in level of detail 4, and modeling data is able to be constructed based on various raw data which are as-built drawing, laser scanning, BIM data, and camera. 3D indoor space modeling has been worked based on established indoor space modeling process, and the result can be used for various application fields such as indoor space pedestrian navigation, facility management, disaster management, and so on. However, the modeling process has limitations to perform indoor space modeling efficiently, because the process is complicated and wastes time at modeling work. In this paper, we propose evaluation on practical use of raw data for 3D indoor space modeling purpose on supporting efficient indoor space modeling through analyzing the established process. Therefore, we define the requirements to evaluate the practical use of raw data and propose the verification method. In addition, as-built drawing which has been used in Seoul 3D indoor space modeling project will be applied to proposed method as a raw data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.499-505
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• 2018

Most of 3D indoor spatial data recently constructed by many projects merely focus on the visualization rather than geospatial information applications. The 3D indoor data for visualization in 3DS or COLLADA format are based on triangular mesh representation. In order to implement meaningful applications, we need however more meaningful information in 3D indoor spatial data than visualization data in triangular meshes. For this reason, an OGC (Open Geospatial Consortium) standard, called IndoorGML(Indoor Geographic Markup Language) was published to meet the requirements on 3D indoor spatial data for several geospatial applications for indoor space more than simple visualization. It means that it becomes a critical functional requirement to convert triangular mesh representation in 3DS or COLLADA to IndoorGML. In this paper we propose a framework of the conversion, which consists of geometric, topological, and semantic construction of data from triangular meshes. An experiment carried out to validate the proposed framework is also presented in the paper.

• Spatial Information Research
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• v.21 no.2
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• pp.11-21
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• 2013

W ith the recent increasing build and application for 3D spatial information, the importance of management and application for spatial information based on indoor space has been increased. Especially, Due to the increasing of the scale and complexity of the building according to the development of construction technologies several studies have been conducted to provide the services based on indoor space such as indoor navigation for disaster. Therefore, to efficient manage and service for information of complicated indoor space, it is necessary to extend and develop 3D spatial model and services that have been developed for outdoor space. In this paper, Indoor Spatial Data Model(ISDM) is developed to support building spatial information for complicated indoor space and location based services through topological information. ISDM contains a feature model which is a CityGML Application Domain Extension(ADE) model and a topology model that refers the IndoorGML.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.297-311
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• 2021

Around the world, there is an increasing interest in Digital Twin cities. Although geospatial data is critical for building a digital twin city, currently-established spatial data cannot be used directly for its implementation. Integration of geospatial data is vital in order to construct and simulate the virtual space. Existing studies for data integration have focused on data transformation. The conversion method is fundamental and convenient, but the information loss during this process remains a limitation. With this, standardization of the data model is an approach to solve the integration problem while hurdling conversion limitations. However, the standardization within indoor space data models is still insufficient compared to 3D building and city models. Therefore, in this study, we present a comparative analysis of data models commonly used in indoor space modeling as a basis for establishing a generic indoor space feature model. By comparing five models of IFC (Industry Foundation Classes), CityGML (City Geographic Markup Language), AIIM (ArcGIS Indoors Information Model), IMDF (Indoor Mapping Data Format), and OmniClass, we identify essential elements for modeling indoor space and the feature classes commonly included in the models. The proposed generic model can serve as a basis for developing further indoor feature models through specifying minimum required structure and feature classes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2381-2398
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• 2024

The construction of virtual indoor spaces is crucial for the development of metaverses, virtual production, and other 3D content domains. Traditional methods for creating these spaces are often cost-prohibitive and labor-intensive. To address these challenges, we present a pipeline for generating digital twins of real indoor environments from RGB-D camera-scanned data. Our pipeline synergizes space structure estimation, 3D object detection, and the inpainting of missing areas, utilizing deep learning technologies to automate the creation process. Specifically, we apply deep learning models for object recognition and area inpainting, significantly enhancing the accuracy and efficiency of virtual space construction. Our approach minimizes manual labor and reduces costs, paving the way for the creation of metaverse spaces that closely mimic real-world environments. Experimental results demonstrate the effectiveness of our deep learning applications in overcoming traditional obstacles in digital twin creation, offering high-fidelity digital replicas of indoor spaces. This advancement opens for immersive and realistic virtual content creation, showcasing the potential of deep learning in the field of virtual space construction.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.591-598
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• 2020

The all revision of the Road Name Address Act, which contains the contents to be used by expanding the road name address as a means of indicationg the location, has been resloved by the National Assembly. Addresses will be assigned to large-sized facilities (3D mixed-use complex spaces). Here, the 3D (Three-dimensional) address is assigned an indoor path section in the inner passage, dividing the section at intervals. The 3D address will be built on the address information map. For 3D address, data should be built and managed for a 3D complex space(indoor space). Therefore, in this study, the object of the 3D address is defined based on the address conceptual model defined in the international standard, and the 3D address data model is proposed based on IndoorGML. To this, it is proposed as a method of mapping the Core and Navigation module of IndoorGML so that the entity of the 3D address can be expressed in IndoorGML. This study has a limitation in designing a 3D address data model only, but it is meaningful that it suggested a standard for constructing 3D address data in the future.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.359-366
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• 2019

Indoor spatial data has great importance as the demand for representing the complex urban environment in the context of providing LBS (Location-based Services) is increasing. IndoorGML (Indoor Geographic Markup Language) has been established as the data standard for spatial data in providing indoor navigation, but its definitions and relationships must be expanded to increase its applications and to successfully delivering information to users. In this study, we propose an approach to integrate IndoorGML with Indoor POI (Points of Interest) data by extending the IndoorGML notion of space and topological relationships. We consider two cases of representing Indoor POI, by 3D geometry and by point primitive representation. Using the concepts of the NRS (node-relation structure) and multi-layered space representation of IndoorGML, we define layers to separate features that represent the spaces and the Indoor POI into separate, but related layers. The proposed methodology was implemented with real datasets to evaluate its effectiveness for performing indoor spatial analysis.

• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.112-116
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• 2008

This paper presents URS (Ubiquitous Robotic Space) Modeling and service technique for the robotic security service while bridging between virtual space and physical space. First, this paper introduces a concept of virtual URS and responsive virtual URS. Second, this paper addresses modeling of URS which covers modeling of indoor geometry and environment sensor. Third, this paper describes virtual URS services including interactive virual-physical bridging service.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.3
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• pp.11-18
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• 2007

Recently 3D GIS and its applications are getting attention increasingly as various ubiquitous-related techniques for 3D spaces are being developed. Although they call for quantitative measures such as accessibility, most accessibilityrelated studies are limited to 2D networks, not 3D indoor space levels. In this paper, we develop an accessibility index applicable to 3D models. We first examine the theory of Space Syntax which has been developed and used to measure the connectivity or relationships between spatial segments in urban or architectural environments. Then, we expand the principle to a more general form so it can be applied to both street and indoor space levels. We incorporate different types of impedances in moving between places including distances, turns and transfers between floors into the traditional Space Syntax that measures the spatial depths solely based on the structural forms. Finally, we illustrate the use of the proposed measure comparatively using a campus building.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.611-622
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• 2020

As the advancement of technologies on indoor positioning systems and measuring devices such as LiDAR (Light Detection And Ranging) and cameras, the demands on analyzing and searching indoor spaces and visualization services via virtual and augmented reality have rapidly increasing. To this end, it is necessary to model 3D objects from measured data from real-world structures. In addition, it is important to store these structured data in standardized formats to improve the applicability and interoperability. In this paper, we propose a method to construct IndoorGML data, which is an international standard for indoor modeling, from point cloud data acquired from LiDAR sensors. After examining considerations that should be addressed in IndoorGML data, we present a construction method, which consists of free space extraction and connectivity detection processes. With experimental results, we demonstrate that the proposed method can effectively reconstruct the 3D model from point cloud.