EXTRACTION OF THE 3D FREE SPACE FROM BUILDING MODELS FOR INDOOR NAVIGATION
For several decades, indoor navigation has been exclusively investigated in a 2D perspective, based on floor plans, projection and other 2D representations of buildings. Nevertheless, 3D representations are closer to our reality and offer a more intuitive description of the space configuration. Than...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2016-10-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-2-W1/241/2016/isprs-annals-IV-2-W1-241-2016.pdf |
| Summary: | For several decades, indoor navigation has been exclusively investigated in a 2D perspective, based on floor plans, projection and other
2D representations of buildings. Nevertheless, 3D representations are closer to our reality and offer a more intuitive description of the
space configuration. Thanks to recent advances in 3D modelling, 3D navigation is timidly but increasingly gaining in interest through
the indoor applications. But, because the structure of indoor environment is often more complex than outdoor, very simplified models
are used and obstacles are not considered for indoor navigation leading to limited possibilities in complex buildings. In this paper
we consider the entire configuration of the indoor environment in 3D and introduce a method to extract from it the actual navigable
space as a network of connected 3D spaces (volumes). We describe how to construct such 3D free spaces from semantically rich and
furnished IFC models. The approach combines the geometric, the topological and the semantic information available in a 3D model to
isolate the free space from the rest of the components. Furthermore, the extraction of such navigable spaces in building models lacking
of semantic information is also considered. A data structure named combinatorial maps is used to support the operations required by
the process while preserving the topological and semantic information of the input models. |
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| ISSN: | 2194-9042 2194-9050 |