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\begin{document}

\title{Enhancing Multi-View 3D Reconstruction of Plant Roots using
Super-Resolution and 3D Gaussian Splatting}



\author[1]{Shangpeng Sun}%
\author[1]{Yuyang Zhang}%
\author[1]{Xuehai Zhou}%
\author[1]{Davoud Torkamaneh}%
\affil[1]{Affiliation not available}%


\vspace{-1em}



  
  \date{May 27, 2024}


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\selectlanguage{english}
\begin{abstract}
Quantifying 3D phenotypic traits for plant shoots and roots is essential
to monitor and evaluate plant growth and development. Multi-view stereo
(MVS) is a low-cost and widely used photogrammetry method to build 3D
point clouds in many agricultural applications. However, it is
challenging to adopt MVS directly to obtain complete 3D structures of
fine roots for plants such as soybeans. To address this problem, we
propose a data processing pipeline incorporating super-resolution (SR)
and 3D Gaussian Splatting (GS) to enhance the resolution of 3D root
reconstruction, aiming to recover a highly detailed 3D root structure.
To this end, first, multi-view images of a soybean root are collected
using an RGB camera; second, SR is used to optimize the resolution of
the images; third, the processed images are fed to the algorithm
structure from motion to obtain a point cloud; and then, 3D GS is
applied to enhance the implicit 3D surface reconstruction; finally,
perceptual similarity and peak signal-to-noise ratio (PSNR) are used to
evaluate the output quality. The method is expected to obtain a
high-fidelity 3D reconstruction of plant roots for soybeans and other
crops, assisting in the extraction of comprehensive phenotypic traits to
accelerate the selection of new varieties for plant breeding.%
\end{abstract}%



\sloppy


\emph{Yuyang Zhang\textsuperscript{1}, \textbf{Shangpeng
Sun\textsuperscript{1}}, Xuehai Zhou\textsuperscript{1}, \emph{Davoud}
Torkamaneh \textsuperscript{2}}

\emph{\textsuperscript{1}Bioresource Engineering Department, McGill
University, QC, Canada}

\selectlanguage{ngerman}\emph{\textsuperscript{2}Département de Phytologie, Université Laval,
QC, Canada}

\textbf{ORCiD:} {[}0000-0001-7095-8626{]}

\textbf{Keywords:} 3D root reconstruction, super-resolution, 3D Gaussian
Splatting, plant phenotyping, point cloud.

\selectlanguage{english}
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