PLANesT-3D: A new annotated data set of 3D color point clouds of plants

Mertoglu K., Salk Y., Sarikaya S. K., TURGUT K., EVRENOSOĞLU Y., ÇEVİKALP H., ...More

31st IEEE Conference on Signal Processing and Communications Applications (SIU), İstanbul, Turkey, 5 - 08 July 2023, (Full Text) identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu59756.2023.10223838
  • City: İstanbul
  • Country: Turkey
  • Keywords: 3D point cloud, 3D plant modeling, 3D plant dataset, 3D semantic segmentation
  • Eskisehir Osmangazi University Affiliated: Yes

Abstract

In this paper, we introduce a new data set, named as PLANesT-3D, which includes complete 3D color point clouds of plants. PLANesT-3D is composed of 34 point clouds acquired from three different plant species: Pepper, rosebush and ribes. The point clouds were reconstructed from 2D color images of real plants through multiview stereo. Through a semi-automatic process, background and noise removal was performed. The point clouds were scaled to their true metric dimensions and brought to a particular pose. Each point in the point clouds was manually labeled into "leaf" and "stem" classes. Also, each leaf instance was assigned a leaf identification number. In order to provide benchmark semantic segmentation performance, segmentation results obtained with the application of PointNet++ are reported. We believe that PLANesT-3D data set will contribute to the development and assessment of segmentation methods that operate on 3D color plant point clouds.