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Authors: Steffen Herbort and Christian Wöhler

Affiliation: TU Dortmund, Germany

ISBN: 978-989-8565-04-4

Keyword(s): 3D Surface Reconstruction, Active Range Scanning, Image-based 3D Reconstruction, Data Fusion, Reflectance Model Estimation.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Geometry and Modeling ; Image-Based Modeling ; Motion, Tracking and Stereo Vision ; Pattern Recognition ; Software Engineering ; Stereo Vision and Structure from Motion

Abstract: 3D surface reconstruction data measured with active range scanners typically suffer from high-frequency noise on small scales. This poses a problem for highly demanding surface inspection tasks and all other applications that require a high accuracy of the depth data. One way to achieve increased 3D reconstruction accuracy is the fusion of active range scanning data and photometric image information. Typically, this requires modeling of the surface reflectance behavior, which, in turn, implies the surface to be known with high accuracy to determine valid reflectance parameters as long as no calibration object is available. In this study, we propose an approach that provides a detailed 3D surface reconstruction along with simultaneously estimated parameters of the reflectance model. For 3D surface reconstruction, we employ an algorithm that combines active range scanning data for large-scale accuracy with image-based information for small-scale accuracy. For inferring the reflectance f unction, we incorporate the estimation of the reflectance model into a self-consistent computational scheme that successively increases the resolution and thus determines the reflectance parameters based on refined depth information. We present results for a homogeneous dark rough metallic surface, which is reconstructed based on a single coarse 3D scan and 12 images acquired under different illumination conditions. (More)

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Paper citation in several formats:
Herbort, S. and Wöhler, C. (2012). SELF-CONSISTENT 3D SURFACE RECONSTRUCTION AND REFLECTANCE MODEL ESTIMATION OF METALLIC SURFACES.In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-04-4, pages 114-121. DOI: 10.5220/0003819701140121

@conference{visapp12,
author={Steffen Herbort. and Christian Wöhler.},
title={SELF-CONSISTENT 3D SURFACE RECONSTRUCTION AND REFLECTANCE MODEL ESTIMATION OF METALLIC SURFACES},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={114-121},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003819701140121},
isbn={978-989-8565-04-4},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)
TI - SELF-CONSISTENT 3D SURFACE RECONSTRUCTION AND REFLECTANCE MODEL ESTIMATION OF METALLIC SURFACES
SN - 978-989-8565-04-4
AU - Herbort, S.
AU - Wöhler, C.
PY - 2012
SP - 114
EP - 121
DO - 10.5220/0003819701140121

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