Volume II-3/W2
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W2, 43-48, 2013
https://doi.org/10.5194/isprsannals-II-3-W2-43-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W2, 43-48, 2013
https://doi.org/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

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 S. Urban et al.
  • 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.