Abdoulaye A. Diakité

Topological reconstruction of complex 3D buildings and automatic extraction of levels of detail

This paper describes a new method allowing to retrieve the indoor and outdoor topology of a detailed 3D building model from its geometry and to extract different levels of detail (LoD) from the resulting topological description. No prior information about the initial model, except its geometric information is needed as input, and using the combinatorial maps data structure, the method recovers the topological information of the identified parts of the building. The topology is needed for most of the applications using 3D building models after the architects design it. While classical models available are mainly furnished in a Boundary Representation (B-Rep) format, we discuss how to recover the components that allow to distinguish the several parts of the building (defined as volumes) then the spatial relationships linking them.

Spatial subdivision of complex indoor environments for 3D indoor navigation

ABSTRACT As we realize that we spend most of our time in increasingly complex indoor environments, applications to assist indoor activities (e.g. guidance) have gained a lot of attention in the recent years. The advances in ubiquitous computing made possible the development of several spatial models intending to support context-aware and fine-grained indoor navigation systems. However, the available models often rely on simplified representations (e.g. 2D plans) and ignore the indoor features (e.g. furniture), thereby missing to reflect the complexity of the indoor environment. In this paper, we introduce the Flexible Space Subdivision framework (FSS) that allows to automatically identify the spaces that can be used for indoor navigation purpose. We propose a classification of indoor objects based on their ability to autonomously change location and we define a spatial subdivision of the indoor environment based on the classified objects and their functions. The framework can consider any 3D indoor configuration, the static and dynamic activities it hosts and it enables the possibility to consider all types of locomotion (e.g. walking, flying, etc.). It relies on input 3D models with geometric, semantic and topological information and identifies a set of subspaces with dedicated properties. We assess the framework against criteria defined in previous researches and we provide an example.

Valid Space Description in BIM for 3D Indoor Navigation

The BIM paradigm, supplied by appropriate standards like IFC, became unavoidable in recent construction projects. Several applications (e.g. indoor navigation, energy analysis ...) find in it a source of information on which they can rely. However, practices reveal that BIM models are not always directly reliable for applications and the latter have to ensure the validity of the data by their own. In the case of indoor navigation, the calculations will highly rely on the IfcSpace objects describing the rooms, in addition to their spatial relationships with their surrounding components. Unfortunately, it is common to face IFC models in which IfcSpace objects contain wrong geometric and topological description. In this paper, the authors discuss the issues related to BIM models validation for indoor navigation. Furthermore, they present a method to generate valid indoor spaces in IFC models. The approach relies on the structural components of the building (walls, slabs, etc.) and uses topological operations, supported by the combinatorial map data structure, to produce watertight space volumes.

Semantic enrichment of octree structured point clouds for multi-story 3D pathfinding

3D indoor navigation in multi-story buildings and under changing environments is still difficult to perform. 3D models of buildings are commonly not available or outdated. 3D point clouds turned out to be a very practical way to capture 3D interior spaces and provide a notion of an empty space. Therefore, pathfinding in point clouds is rapidly emerging. However, processing of raw point clouds can be very expensive, as these are semantically poor and unstructured data. In this article we present an innovative octree-based approach for processing of 3D indoor point clouds for the purpose of multi-story pathfinding. We semantically identify the construction elements, which are of importance for the indoor navigation of humans (i.e., floors, walls, stairs, and obstacles), and use these to delineate the available navigable space. To illustrate the usability of this approach, we applied it to real-world data sets and computed paths considering user constraints. The structuring of the point cloud into an octree approximation improves the point cloud processing and provides a structure for the empty space of the point cloud. It is also helpful to compute paths sufficiently accurate in their consideration of the spatial complexity. The entire process is automatic and able to deal with a large number of multi-story indoor environments.

Processing BIM and GIS models in practice: experiences and recommendations from a GeoBIM project in the Netherlands

It is widely acknowledged that the integration of BIM and GIS data is a crucial step forward for future 3D city modelling, but most of the research conducted so far has covered only the high-level and semantic aspects of GIS-BIM integration. This paper presents the results of the GeoBIM project, which tackled three integration problems focussing instead on aspects involving geometry processing: (i) the automated processing of complex architectural IFC models; (ii) the integration of existing GIS subsoil data in BIM; and (iii) the georeferencing of BIM models for their use in GIS software. All the problems have been studied using real world models and existing datasets made and used by practitioners in The Netherlands. For each problem, this paper exposes in detail the issues faced, proposed solutions, and recommendations for a more successful integration.