The Open Geospatial Consortium (OGC) Geography Markup Language (GML) standard provides basic types and a framework for defining geo-informational data models such as CityGML and IndoorGML, which provide standard information models for 3D city modelling and lightweight indoor network navigation. Location information, which is the semantic engine that fuses big geo-information data, is however, discarded in these standards. The Chinese national standard of Indoor Multi-Dimensional Location GML (IndoorLocationGML) presented in this study can be used in ubiquitous indoor location intelligent applications for people and robots. IndoorLocationGML is intended as an indoor multi-dimensional location information model and exchange data format standard, mainly for indoor positioning and navigation. This paper introduces the standard’s main features: (1) terminology; (2) indoor location information model using a Unified Modeling Language (UML) class diagram; (3) indoor location information markup language based on GML; and (4) use cases. A typical application of the standard is then discussed. This standard is applicable to the expression, storage, and distribution of indoor multi-dimensional location information, and to the seamless integration of indoor–outdoor location information. The reference and basis are therefore relevant to publishers, managers, users, and developers of indoor navigation and location-based services (LBS)@en

Video surveillance systems are increasingly used for a variety of 3D indoor applications. We can analyse human behaviour, discover and avoid crowded areas, monitor human traffic and so forth. In this paper we concentrate on use of surveillance cameras to track and reconstruct the path a person has followed. For the purpose we integrated video surveillance data with a 3D indoor model of the building and develop a single human moving path tracking method. We process the surveillance videos to detected single human moving traces; then we match the depth information of 3D scenes to the constructed 3D indoor network model and define the human traces in the 3D indoor space. Finally, the single human traces extracted from multiple cameras are connected with the help of the connectivity provided by the 3D network model. Using this approach, we can reconstruct the entire walking path. The provided experiments with a single person have verified the effectiveness and robustness of the method@en

Intelligent navigation and facility management in complex indoor environments are issues at the forefront of geospatial information science. Indoor spaces with fine geometric and semantic descriptions provide a solid foundation for various indoor applications, but it is difficult to comprehensively extract free multi-floor indoor spaces from complex three-dimensional building models, such as those described using CityGML LoD4, with existing methods for the subdivision or extraction of indoor spaces based on vector topology processing. Therefore, this paper elaborates a new voxelbased approach for extracting free multi-floor indoor spaces from 3D building models. It transforms the complicated vector processing tasks into a simple raster process that consists of three steps: voxelization with semantic enhancement, voxel classification, and boundary extraction. Experiments illustrate that the proposed method can automatically and correctly extract free multi-floor indoor spaces, especially two typical kinds of open indoor spaces, namely, lobbies and staircases.@en