Fruit detection and 3D location in photogrammetry-derived 3D point clouds

Introduction

This project is a matlab implementation to project image detections (instance segmentation masks) onto 3D point clouds generated using structure-from-motion. This code was used in [1] to locate fruits by using the Fuji-SfM dataset. Find more information in:

• Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry [1].

Preparation

First of all, create a new project folder:

mkdir new_project

Then, clone the code inside “new_project” folder:

cd new_project
git clone https://github.com/GRAP-UdL-AT/SfM_3D_fruit_detection.git

Prerequisites

• MATLAB R2021a (we have not tested it in other matlab versions)
• Computer Vision System Toolbox
• Statistics and Machine Learning Toolbox

Data Preparation

Inside the “new_project” folder, save the dataset folder “data” available at download data.

Launch the code

• Execute the file /new_project/ SfM_3D_fruit_detection/ main_SfM_3D_fruit_detection.m

Authorship

This project is contributed by GRAP-UdL-AT.

Please contact authors to report bugs @ [email protected]

Citation

If you find this implementation or the analysis conducted in our report helpful, please consider citing:

@article{Gené-Mola2021a,
    Author = {{Gen{\'e}-Mola, Jordi and Sanz-Cortiella, Ricardo and Rosell-Polo, Joan R and Morros, Josep-Ramon and Ruiz-Hidalgo, Javier and Vilaplana, Ver{\’o}nica and Gregorio, Eduard },
    Title = { Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry },
    Journal = {Computers and Electronics in Agriculture},
    Year = {2020}
    doi = {https://doi.org/10.1016/j.compag.2019.105165 }
}

@article{Gené-Mola2021b,
    Author = {{Gen{\'e}-Mola, Jordi and Sanz-Cortiella, Ricardo and Rosell-Polo, Joan R and Morros, Josep-Ramon and Ruiz-Hidalgo, Javier and Vilaplana, Ver{\’o}nica and Gregorio, Eduard },
    Title = { Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry},
    Journal = {Data in Brief},
    Year = {2020}
    doi = { https://doi.org/10.1016/j.dib.2020.105591}
}

Acknowledgements

This work was partly funded by the Spanish Ministry of Science, Innovation and Universities (grant RTI2018-094222-B-I00[PAgFRUIT project] by MCIN/AEI/10.13039/501100011033 and by “ERDF, a way of making Europe”, by the European Union).