点云
分割
人工智能
计算机科学
计算机视觉
水准点(测量)
数据集
噪音(视频)
集合(抽象数据类型)
点(几何)
公制(单位)
地理
数学
工程类
地图学
图像(数学)
程序设计语言
运营管理
几何学
作者
Kerem Mertoğlu,Yusuf Şalk,Server Karahan Sarıkaya,Kaya Turgut,Yasemin Evrenosoğlu,Hakan Çevıkalp,Ömer Nezih Gerek,Helin Dutağacı,David Rousseau
标识
DOI:10.1109/siu59756.2023.10223838
摘要
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.
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