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Authors: Min Li ; Changyu Diao ; Song Lv and Dongming Lu

Affiliation: Zhejiang University, China

Keyword(s): Structured-light, Photometric Stereo, Convex Optimization, 3D Reconstruction.

Related Ontology Subjects/Areas/Topics: Applications ; Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Geometry and Modeling ; Image-Based Modeling ; Imaging for Cultural Heritage (Modeling/Simulation, Virtual Restoration) ; Pattern Recognition ; Software Engineering

Abstract: We present a convex framework to acquire high resolution surfaces. It is typical to couple a structure-light setup and a photometric method to reconstruct a high resolution 3D surface. Previous methods often get stuck in a local minima for the appearance of occasional outliers. To address this issue, we develop a convex variational model by incorporating a total variation (TV) regularization term with a data term to generate the surface. Through relaxing the model to an equivalent high dimensional variational problem, we obtain a global minimizer of the proposed problem. Results on both synthetic and real-world data show an excellent performance by utilizing our convex variational model.

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Paper citation in several formats:
Li, M.; Diao, C.; Lv, S. and Lu, D. (2015). A Convex Framework for High Resolution 3D Reconstruction. In Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 1: VISAPP; ISBN 978-989-758-091-8; ISSN 2184-4321, SciTePress, pages 317-324. DOI: 10.5220/0005306503170324

@conference{visapp15,
author={Min Li. and Changyu Diao. and Song Lv. and Dongming Lu.},
title={A Convex Framework for High Resolution 3D Reconstruction},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 1: VISAPP},
year={2015},
pages={317-324},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005306503170324},
isbn={978-989-758-091-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 1: VISAPP
TI - A Convex Framework for High Resolution 3D Reconstruction
SN - 978-989-758-091-8
IS - 2184-4321
AU - Li, M.
AU - Diao, C.
AU - Lv, S.
AU - Lu, D.
PY - 2015
SP - 317
EP - 324
DO - 10.5220/0005306503170324
PB - SciTePress

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