Branch-pipe: Improving graph skeletonization around branch points in 3D point clouds

Ziamtsov, I, Faizi, K, Navlakha, S (September 2021) Branch-pipe: Improving graph skeletonization around branch points in 3D point clouds. Remote Sensing, 13 (19). ISSN 2072-4292

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DOI: 10.3390/rs13193802

Abstract

Modern plant phenotyping requires tools that are robust to noise and missing data, while being able to efficiently process large numbers of plants. Here, we studied the skeletonization of plant architectures from 3D point clouds, which is critical for many downstream tasks, including analyses of plant shape, morphology, and branching angles. Specifically, we developed an algorithm to improve skeletonization at branch points (forks) by leveraging the geometric properties of cylinders around branch points. We tested this algorithm on a diverse set of high-resolution 3D point clouds of tomato and tobacco plants, grown in five environments and across multiple developmental timepoints. Compared to existing methods for 3D skeletonization, our method efficiently and more accurately estimated branching angles even in areas with noisy, missing, or non-uniformly sampled data. Our method is also applicable to inorganic datasets, such as scans of industrial pipes or urban scenes containing networks of complex cylindrical shapes.

Item Type: Paper
Subjects: bioinformatics > computational biology
organism description > plant
CSHL Authors:
Communities: CSHL labs > Navlakha lab
SWORD Depositor: CSHL Elements
Depositing User: CSHL Elements
Date: 22 September 2021
Date Deposited: 06 Oct 2021 15:42
Last Modified: 06 Oct 2021 15:42
URI: https://repository.cshl.edu/id/eprint/40379

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