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Communication Dans Un Congrès Année : 2017

Leaves segmentation in 3D point cloud

Résumé

This paper presents a 3D plant segmentation method with an empathy especially put on the leaves segmentation. This method is part of a 3D plant phenotyping project with a main objective that deals with the evolution of the leaf area over time. First, a 3D point cloud of a plant is obtained with Structure from Motion technique and then, the main parts of a plan, here: the stem and the leaves, are segmented in the 3D point cloud. As the main objective is to compute the leaf area over time, the empathy was put on the segmentation and the labelling of the leaves. This article presents an original approach which starts by finding the stem in a 3D point cloud and then the leaves. Moreover, this method relies on the model of a plant as well as the agronomic rules to affect a unique label that do not change over time. This method is evaluated through two plants, sunflower and sorghum.
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Dates et versions

hal-02738450 , version 1 (02-06-2020)

Identifiants

Citer

William Gelard, Ariane Herbulot, Michel Devy, Philippe Debaeke, Ryan F. Mccormick, et al.. Leaves segmentation in 3D point cloud. 18. International Conference, ACIVS 2017, Sep 2017, Antwerp, Belgium. 763 p., ⟨10.1007/978-3-319-70353-4_56⟩. ⟨hal-02738450⟩
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