Abstract
Feature-based 3D reconstruction methods only work reliably for images with enough features (i.e., texture) that can be matched to infer a depth map. Contradicting the core assumption of such methods, the 3D reconstruction of objects with textureless surfaces remains challenging. This paper explores a simple solution to this problem, i.e., adding artificial texture to such objects. In particular, we equipped a multi-view stereo based inline computational imaging system with a pattern illumination module to compensate for the absence of texture. Comparisons of 3D reconstructions from acquisitions with and without projected patterns show an increase in accuracy when using the pattern illumination.
Originalsprache | Englisch |
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Titel | Computer Vision Systems |
Untertitel | Proceedings of the 14th International Conference on Computer Vision Systems (ICVS 2023) |
Redakteure/-innen | Henrik I. Christensen, Peter Corke, Renaud Detry, Jean-Baptiste Weibel, Markus Vincze |
Seiten | 412-421 |
Seitenumfang | 10 |
Band | 14253 |
ISBN (elektronisch) | 978-3-031-44137-0 |
DOIs | |
Publikationsstatus | Veröffentlicht - 21 Sept. 2023 |
Veranstaltung | 14th International Conference on Computer Vision Systems (ICVS 2023) - Vienna University of Technology, Vienna, Österreich Dauer: 27 Sept. 2023 → 29 Sept. 2023 https://icvs2023.conf.tuwien.ac.at/ |
Publikationsreihe
Name | Lecture Notes in Computer Science |
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Herausgeber (Verlag) | Springer Cham |
Band | 14253 |
ISSN (Print) | 0302-9743 |
ISSN (elektronisch) | 1611-3349 |
Konferenz
Konferenz | 14th International Conference on Computer Vision Systems (ICVS 2023) |
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Land/Gebiet | Österreich |
Stadt | Vienna |
Zeitraum | 27/09/23 → 29/09/23 |
Internetadresse |
Research Field
- High-Performance Vision Systems