Reflective surface reconstruction from inverse deflectometric measurements

Penk D, Sturm R, Seifert L, Stamminger M, Greiner G (2020)


Publication Type: Conference contribution

Publication year: 2020

Publisher: SciTePress

Book Volume: 4

Pages Range: 76-84

Conference Proceedings Title: VISIGRAPP 2020 - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications

Event location: Valletta MT

ISBN: 9789897584022

DOI: 10.5220/0008968600760084

Abstract

Reconstructing reflective surfaces is a difficult task since most algorithms rely on photometric consistency between multiple views on the target object. However specular reflections are highly view dependent and thus violate this assumption. Previous work therefore often incorporates additional information, like polarization or the distortion of a known pattern, to perform specular surface reconstruction. We present a novel analysis by synthesis approach that defines an optimization problem using samples directly on the reconstructed surface. Based on this framework we describe two different setups for reconstruction, one using a line laser to create a reflection pattern and a second one, that uses point measurements to provide ray-measurement correspondences achieving improved accuracy.

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How to cite

APA:

Penk, D., Sturm, R., Seifert, L., Stamminger, M., & Greiner, G. (2020). Reflective surface reconstruction from inverse deflectometric measurements. In Giovanni Maria Farinella, Petia Radeva, Jose Braz (Eds.), VISIGRAPP 2020 - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (pp. 76-84). Valletta, MT: SciTePress.

MLA:

Penk, Dominik, et al. "Reflective surface reconstruction from inverse deflectometric measurements." Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2020, Valletta Ed. Giovanni Maria Farinella, Petia Radeva, Jose Braz, SciTePress, 2020. 76-84.

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