Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W4, 131-137, 2015
https://doi.org/10.5194/isprsarchives-XL-5-W4-131-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
18 Feb 2015
AUTOMATIC TEXTURE AND ORTHOPHOTO GENERATION FROM REGISTERED PANORAMIC VIEWS
U. Krispel2,1, H. L. Evers2, M. Tamke2, R. Viehauser3, and D. W. Fellner4,5 1Fraunhofer Austria, Graz, Austria
2Centre for Information Technology and Architecture (CITA), Copenhagen, Denmark
3Institute for Computer Graphics and Vision (ICG), TU Graz, Austria
4Institute of ComputerGraphics and KnowledgeVisualization (CGV), TU Graz, Austria
5GRIS, TU Darmstadt & Fraunhofer IGD, Darmstadt, Germany
Keywords: spherical panorama, image registration, texturing, point clouds, machine learning, automated generation of semantic information Abstract. Recent trends in 3D scanning are aimed at the fusion of range data and color information from images. The combination of these two outputs allows to extract novel semantic information. The workflow presented in this paper allows to detect objects, such as light switches, that are hard to identify from range data only. In order to detect these elements, we developed a method that utilizes range data and color information from high-resolution panoramic images of indoor scenes, taken at the scanners position. A proxy geometry is derived from the point clouds; orthographic views of the scene are automatically identified from the geometry and an image per view is created via projection. We combine methods of computer vision to train a classifier to detect the objects of interest from these orthographic views. Furthermore, these views can be used for automatic texturing of the proxy geometry.
Conference paper (PDF, 2598 KB)


Citation: Krispel, U., Evers, H. L., Tamke, M., Viehauser, R., and Fellner, D. W.: AUTOMATIC TEXTURE AND ORTHOPHOTO GENERATION FROM REGISTERED PANORAMIC VIEWS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W4, 131-137, https://doi.org/10.5194/isprsarchives-XL-5-W4-131-2015, 2015.

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