Combined Grammar for the Modeling of Building Interiors
As spatial grammars have proven successful and efficient to deliver LOD3 models, the next challenge is their extension to indoor applications, leading to LOD4 models. Therefore, a combined indoor grammar for the automatic generation of indoor models from erroneous and incomplete observation data is...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2013-11-01
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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/II-4-W1/1/2013/isprsannals-II-4-W1-1-2013.pdf |
| Summary: | As spatial grammars have proven successful and efficient to deliver LOD3 models, the next challenge is their extension to indoor
applications, leading to LOD4 models. Therefore, a combined indoor grammar for the automatic generation of indoor models from
erroneous and incomplete observation data is presented. In building interiors where inaccurate observation data is available, the
grammar can be used to make the reconstruction process robust, and verify the reconstructed geometries. In unobserved building
interiors, the grammar can generate hypotheses about possible indoor geometries matching the style of the rest of the building. The
grammar combines concepts from L-systems and split grammars. It is designed in such way that it can be derived from observation
data fully automatically. Thus, manual predefinitions of the grammar rules usually required to tune the grammar to a specific
building style, become obsolete. The potential benefit of using our grammar as support for indoor modeling is evaluated based on an
example where the grammar has been applied to automatically generate an indoor model from erroneous and incomplete traces
gathered by foot-mounted MEMS/IMU positioning systems. |
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| ISSN: | 2194-9042 2194-9050 |