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  4. AI Based Image Segmentation of Cultural Heritage Objects used for Multi-View Stereo 3D Reconstructions
 
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2023
Conference Paper
Title

AI Based Image Segmentation of Cultural Heritage Objects used for Multi-View Stereo 3D Reconstructions

Abstract
Image segmentation (or masking) finds a very useful use case within 3D reconstruction of cultural heritage objects. The 3D reconstructions can be accelerated, reconstructing the object without any background noise. Conventional segmentation methods can calculate erroneous masks for certain objects and environments, which can lead to errors within the reconstruction: Parts of the 3D reconstruction may be missing or are incorrectly reconstructed, which contradicts adequate archiving. The automated iterative Multi-View Stereo (MVS) scanning process makes it necessary to obtain masks that reconstruct the object in the best possible way, regardless of the environment, the stabilizing mount, the color of the background and the object. In addition, it should not be necessary to tweak the best possible parameters for conventional masking procedures and to create masks manually. State-of-the-art artificial intelligence (AI) segmentation networks will be trained and applied to the MVS scans to verify the behavior of the associated 3D reconstructions and the automated iterative scanning process. In addition, a comparison between different AI segmentation networks and a comparison between conventional masking methods and AI segmentation networks is performed.
Author(s)
Kutlu, Hasan  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Brucker, Felix
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Kallendrusch, Ben
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Santos, Pedro
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Fellner, Dieter
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Mainwork
GCH 2023, Eurographics Workshop on Graphics and Cultural Heritage  
Conference
Workshop on Graphics and Cultural Heritage 2023  
Open Access
DOI
10.2312/gch.20231160
10.24406/publica-1914
File(s)
075-079.pdf (9.1 MB)
Rights
CC BY 4.0: Creative Commons Attribution
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • Branche: Cultural und Creative Economy

  • Research Line: Computer vision (CV)

  • Research Line: Machine learning (ML)

  • LTA: Generation, capture, processing, and output of images and 3D models

  • Artificial intelligence (AI)

  • Automatic segmentation

  • Image segmentation

  • Structure-from-Motion (SfM)

  • 3D Scanning

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