Using t-distributed stochastic neighbor embedding for visualization and segmentation of 3D point clouds of plants

Authors

HELİN DUTAĞACI

DOI

10.55730/1300-0632.4018

Abstract

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 2D implementation of various steps involved in automatic 3D phenotyping pipelines.

Keywords

Point clouds, plants, visualization, superpoint, segmentation, t-distributed stochastic neighbor embedding

First Page

792

Last Page

813

Recommended Citation

DUTAĞACI, HELİN (2023) "Using t-distributed stochastic neighbor embedding for visualization and segmentation of 3D point clouds of plants," Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 31: No. 5, Article 4. https://doi.org/10.55730/1300-0632.4018
Available at: https://journals.tubitak.gov.tr/elektrik/vol31/iss5/4