ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W2, 43-48, 2013
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-3-W2/43/2013/
doi:10.5194/isprsannals-II-3-W2-43-2013
© Author(s) 2013. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
07 Oct 2013
SELF-LOCALIZATION OF A MULTI-FISHEYE CAMERA BASED AUGMENTED REALITY SYSTEM IN TEXTURELESS 3D BUILDING MODELS
S. Urban, J. Leitloff, S. Wursthorn, and S. Hinz Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology, Englerstr. 7, 76137 Karlsruhe, Germany
Keywords: Computer vision, fisheye camera, real-time object detection, model-based tracking, augmented reality Abstract. Georeferenced images help planners to compare and document the progress of underground construction sites. As underground positioning can not rely on GPS/GNSS, we introduce a solely vision based localization method, that makes use of a textureless 3D CAD model of the construction site. In our analysis-by-synthesis approach, depth and normal fisheye images are rendered from presampled positions and gradient orientations are extracted to build a high dimensional synthetic feature space. Acquired camera images are then matched to those features by using a robust distance metric and fast nearest neighbor search. In this manner, initial poses can be obtained on a laptop in real-time using concurrent processing and the graphics processing unit.
Conference paper (PDF, 1540 KB)


Citation: Urban, S., Leitloff, J., Wursthorn, S., and Hinz, S.: SELF-LOCALIZATION OF A MULTI-FISHEYE CAMERA BASED AUGMENTED REALITY SYSTEM IN TEXTURELESS 3D BUILDING MODELS, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W2, 43-48, doi:10.5194/isprsannals-II-3-W2-43-2013, 2013.

BibTeX EndNote Reference Manager XML