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Publication . Other literature type . Article . Conference object . 2018

Automatic texture and orthophoto generation from registered panoramic views

Ulrich Krispel; Henrik Leander Evers; Martin Tamke; R. Viehauser; Dieter W. Fellner;
Open Access
English
Published: 15 Jan 2018
Country: Germany
Abstract
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.
Subjects by Vocabulary

ACM Computing Classification System: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ComputingMethodologies_COMPUTERGRAPHICS

Microsoft Academic Graph classification: Image registration Orthophoto Workflow Orthographic projection Geography Computer vision Point cloud Semantic information Artificial intelligence business.industry business 3d scanning Classifier (UML)

Library of Congress Subject Headings: lcsh:Technology lcsh:T lcsh:Engineering (General). Civil engineering (General) lcsh:TA1-2040 lcsh:Applied optics. Photonics lcsh:TA1501-1820

Subjects

Forschungsgruppe Semantic Models, Immersive Systems (SMIS), Virtual engineering [Business Field], Digital society [Business Field], Computer graphics (CG) [Research Line], Modeling (MOD) [Research Line], image registration, Texturing, point cloud, machine learning

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Funded by
EC| DURAARK
Project
DURAARK
Durable Architectural Knowledge
  • Funder: European Commission (EC)
  • Project Code: 600908
  • Funding stream: FP7 | SP1 | ICT
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