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 -

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.

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