Sensors 2013, 13(2), 2430-2446; doi:10.3390/s130202430
Article

Fusion of Building Information and Range Imaging for Autonomous Location Estimation in Indoor Environments

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Received: 15 October 2012; in revised form: 4 February 2013 / Accepted: 4 February 2013 / Published: 14 February 2013
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: We present a novel approach for autonomous location estimation and navigation in indoor environments using range images and prior scene knowledge from a GIS database (CityGML). What makes this task challenging is the arbitrary relative spatial relation between GIS and Time-of-Flight (ToF) range camera further complicated by a markerless configuration. We propose to estimate the camera’s pose solely based on matching of GIS objects and their detected location in image sequences. We develop a coarse-to-fine matching strategy that is able to match point clouds without any initial parameters. Experiments with a state-of-the-art ToF point cloud show that our proposed method delivers an absolute camera position with decimeter accuracy, which is sufficient for many real-world applications (e.g., collision avoidance).
Keywords: indoor positioning; ToF cameras; range imaging; CityGML; point cloud library
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MDPI and ACS Style

Kohoutek, T.K.; Mautz, R.; Wegner, J.D. Fusion of Building Information and Range Imaging for Autonomous Location Estimation in Indoor Environments. Sensors 2013, 13, 2430-2446.

AMA Style

Kohoutek TK, Mautz R, Wegner JD. Fusion of Building Information and Range Imaging for Autonomous Location Estimation in Indoor Environments. Sensors. 2013; 13(2):2430-2446.

Chicago/Turabian Style

Kohoutek, Tobias K.; Mautz, Rainer; Wegner, Jan D. 2013. "Fusion of Building Information and Range Imaging for Autonomous Location Estimation in Indoor Environments." Sensors 13, no. 2: 2430-2446.


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