In this work, the use of t-SNE is proposed to embed 3D point clouds of plants into 2D space for plant characterization. It is demonstrated that t-SNE operates as a practical tool to flatten and visualize a complete 3D plant model in 2D space. The perplexity parameter of t-SNE allows 2D rendering of plant structures at various organizational levels. Aside from the promise of serving as a visualization tool for plant scientists, t-SNE also provides a gateway for processing 3D point clouds of plants using their embedded counterparts in 2D. In this paper, simple methods were proposed to perform semantic segmentation and instance segmentation via grouping the embedded 2D points. The evaluation of these methods on a public 3D plant data set conveys the potential of t-SNE for enabling of 2D implementation of various steps involved in automatic 3D phenotyping pipelines.

翻译：本研究提出利用t-SNE将植物三维点云嵌入二维空间以实现植物特征表征。研究表明，t-SNE可作为实用工具将完整的三维植物模型展平并可视化于二维空间。t-SNE的困惑度参数能够呈现不同组织层级下的植物结构二维渲染图。除了作为植物科学家的可视化工具外，t-SNE还为处理植物三维点云提供了通过二维嵌入进行处理的途径。本文提出基于嵌入二维点聚类实现语义分割与实例分割的简易方法。在公开植物三维数据集上的评估结果表明，t-SNE具有在自动三维表型分析流程中实现各步骤二维化的潜力。