TY - DATA
T1 - TomatoWUR: an annotated dataset of 3D tomato plants to quantitatively evaluate segmentation, skeletonisation, and plant trait extraction algorithms for 3D plant phenotyping
PY - 2025/04/30
AU - Bart M. Marrewijk, van
AU - Tim van Daalen
AU - Katarína Smoleňová
AU - Bolai Xin
AU - Gerrit Polder
AU - Gert Kootstra
UR - 
DO - 10.4121/e2c59841-4653-45de-a75e-4994b2766a2f.v2
KW - 3D plant phenotyping
KW - horticulture
KW - tomato
KW - segmentation
KW - plant architecture
KW - point clouds
KW - RGB images
KW - 3D phenotyping
KW - shape-from-silhouette
N2 - <p>In this research, we created a dataset of 44 annotated 3D point clouds of tomato plants. Images were captured using fifteen cameras surrounding a single plant. Those images were used to create a point cloud using the shape-from silhouette methodology (Golbach et al., 2016). The resulting dataset was annotated and separated into three parts. 1) Annotated point clouds and corresponding RGB images with semantic and instance labels , 2) annotated skeletons to analyse plant architecture, and 3) manual reference measurements of internode length, internode diameter, leaf angle,  and phyllotactic angle to evaluate phenotyping algorithms from point cloud to plant traits.</p>
ER -