Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-4/W5, 7-11, 2015
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-4-W5/7/2015/
doi:10.5194/isprsarchives-XL-4-W5-7-2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
11 May 2015
AUTOMATIC TOPOLOGY DERIVATION FROM IFC BUILDING MODEL FOR IN-DOOR INTELLIGENT NAVIGATION
S. J. Tang2, Q. Zhu2,3, W. W. Wang1, and Y. T. Zhang2 1Shenzhen research center of digital city engineering, Shenzhen, P.R. China
2State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan, P.R. China
3Faculty of Geosciences and Environmental Engineering of Southwest Jiaotong University, Chengdu, P.R. China
Keywords: IFC, Geometry-Semantics-based, Topology Derivation, Navigation Abstract. With the goal to achieve an accuracy navigation within the building environment, it is critical to explore a feasible way for building the connectivity relationships among 3D geographical features called in-building topology network. Traditional topology construction approaches for indoor space always based on 2D maps or pure geometry model, which remained information insufficient problem. Especially, an intelligent navigation for different applications depends mainly on the precise geometry and semantics of the navigation network. The trouble caused by existed topology construction approaches can be smoothed by employing IFC building model which contains detailed semantic and geometric information. In this paper, we present a method which combined a straight media axis transformation algorithm (S-MAT) with IFC building model to reconstruct indoor geometric topology network. This derived topology aimed at facilitating the decision making for different in-building navigation. In this work, we describe a multi-step deviation process including semantic cleaning, walkable features extraction, Multi-Storey 2D Mapping and S-MAT implementation to automatically generate topography information from existing indoor building model data given in IFC.
Conference paper (PDF, 904 KB)


Citation: Tang, S. J., Zhu, Q., Wang, W. W., and Zhang, Y. T.: AUTOMATIC TOPOLOGY DERIVATION FROM IFC BUILDING MODEL FOR IN-DOOR INTELLIGENT NAVIGATION, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-4/W5, 7-11, doi:10.5194/isprsarchives-XL-4-W5-7-2015, 2015.

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