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Authors: Junjie Hu and Terumasa Aoki

Affiliation: Tohoku University, Japan

ISBN: 978-989-758-227-1

Keyword(s): Non-rigid Structure From Motion, Sparse Representation, l1-norm Minimization.

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: This paper presents a convex solution for simultaneously recovering 3D non-rigid structures and camera motions from 2D image sequences based on sparse representation. Most existing methods rely on low rank assumption. However, it will lead to poor reconstruction for objects with strong local deformation. Also, when camera motion is unknown, there is no convex solution for non-rigid structure from motion (NRSfM). In order to solve this problem, we estimate non-rigid structures by sparse representation. In this paper, we estimate camera motions through a sparse spectral-norm minimization approach, and then a fast l1-norm minimization algorithm is introduced to reconstruct 3D structures. Both of them are convex, therefore, our method gives a global optimum. Our method can handle objects with strong local deformation and also doesn’t need low rank prior. Experimental results show that our method achieves state-of-the-art reconstruction performance on CMU benchmark dataset.

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Paper citation in several formats:
Hu, J. and Aoki, T. (2017). A Convex Approach for Non-rigid Structure from Motion Via Sparse Representation.In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6 VISAPP: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-227-1, pages 333-339. DOI: 10.5220/0006078603330339

@conference{visapp17,
author={Junjie Hu. and Terumasa Aoki.},
title={A Convex Approach for Non-rigid Structure from Motion Via Sparse Representation},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6 VISAPP: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={333-339},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006078603330339},
isbn={978-989-758-227-1},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6 VISAPP: VISAPP, (VISIGRAPP 2017)
TI - A Convex Approach for Non-rigid Structure from Motion Via Sparse Representation
SN - 978-989-758-227-1
AU - Hu, J.
AU - Aoki, T.
PY - 2017
SP - 333
EP - 339
DO - 10.5220/0006078603330339

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