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Authors: William Gelard 1 ; Michel Devy 2 ; Ariane Herbulot 3 and Philippe Burger 4

Affiliations: 1 CNRS, LAAS, Univ. de Toulouse, INRA and AGIR, France ; 2 CNRS and LAAS, France ; 3 CNRS, LAAS and Univ. de Toulouse, France ; 4 INRA and AGIR, France

ISBN: 978-989-758-225-7

Keyword(s): 3D Plant Phenotyping, Structure from Motion, Clustering, Labeling, Nurbs Fitting, Sunflowers.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Geometry and Modeling ; Image and Video Analysis ; Image-Based Modeling ; Pattern Recognition ; Segmentation and Grouping ; Shape Representation and Matching ; Software Engineering

Abstract: This article presents a model-based segmentation method applied to 3D data acquired on sunflower plants. Our objective is the quantification of the plant growth using observations made automatically from sensors moved around plants. Here, acquisitions are made on isolated plants: a 3D point cloud is computed using Structure from Motion with RGB images acquired all around a plant. Then the proposed method is applied in order to segment and label the plant leaves, i.e. to split up the point cloud in regions corresponding to plant organs: stem, petioles, and leaves. Every leaf is then reconstructed with NURBS and its area is computed from the triangular mesh. Our segmentation method is validated comparing these areas with the ones measured manually using a planimeter: it is shown that differences between automatic and manual measurements are less than 10%. The present results open interesting perspectives in direction of high-throughput sunflower phenotyping.

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Paper citation in several formats:
Gelard, W.; Devy, M.; Herbulot, A. and Burger, P. (2017). Model-based Segmentation of 3D Point Clouds for Phenotyping Sunflower Plants.In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-225-7, pages 459-467. DOI: 10.5220/0006126404590467

@conference{visapp17,
author={William Gelard. and Michel Devy. and Ariane Herbulot. and Philippe Burger.},
title={Model-based Segmentation of 3D Point Clouds for Phenotyping Sunflower Plants},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={459-467},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006126404590467},
isbn={978-989-758-225-7},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)
TI - Model-based Segmentation of 3D Point Clouds for Phenotyping Sunflower Plants
SN - 978-989-758-225-7
AU - Gelard, W.
AU - Devy, M.
AU - Herbulot, A.
AU - Burger, P.
PY - 2017
SP - 459
EP - 467
DO - 10.5220/0006126404590467

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