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  4. Context-aware patch-based method for façade inpainting
 
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2020
Conference Paper
Title

Context-aware patch-based method for façade inpainting

Abstract
Realistic representations of 3D urban scenes is an important aspect of scene understanding and has many applications. Given untextured polyhedral Level-of-Detail 2 (LoD2) models of building and imaging containing façade textures, occlusions caused by foreground objects are an essential disturbing factor of façade textures. We developed a modification of a well-known patch-based inpainting method and used the knowledge about façade details in order to improve the façade inpainting of occlusions. Our modification focuses on suppression of undesired, superfluous repetitions of textures. To achieve this, a coarse inpainting result by a structural-based method is used to influence the choice of the best patch so that homogeneous regions are preferred. The coarse inpainting is calculated using the context knowledge and average color instead of traditionally applied arbitrary structural inpainting. Our modification furthermore introduces a parameter that allows to weight the influence of the coarse inpainting. A parameter study shows that this parameter can be chosen intuitively and does not require any parameter choice method. The cleaned façade textures could be successfully integrated into the accordingly adjusted building models thus upgrading them to LoD3.
Author(s)
Kottler, Benedikt  
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Bulatov, Dimitri  
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Xingzi, Zhang
Fraunhofer Singapore  
Mainwork
15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. Proceedings. Vol.1: GRAPP  
Conference
International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP) 2020  
International Conference on Computer Graphics Theory and Applications (GRAPP) 2020  
Open Access
File(s)
Download (5.09 MB)
Rights
CC BY-NC-ND 4.0: Creative Commons Attribution-NonCommercial-NoDerivatives
DOI
10.5220/0008874802100218
10.24406/publica-r-407340
Additional link
Full text
Language
English
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Singapore  
Keyword(s)
  • city modeling

  • inpainting

  • patch-based inpainting

  • texture image

  • Lead Topic: Smart City

  • Research Line: Computer graphics (CG)

  • Research Line: Machine Learning (ML)

  • image enhancement

  • context aware computing

  • image-based reconstruction

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