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Authors: Justin Le Louedec 1 ; Bo Li 2 and Grzegorz Cielniak 1

Affiliations: 1 Lincoln Centre for Autonomous Systems, University of Lincoln, U.K. ; 2 University of West England, U.K.

Keyword(s): Machine Vision for Agriculture, Machine Learning, 3D Sensing, 3D Vision.

Abstract: 3D information provides unique information about shape, localisation and relations between objects, not found in standard 2D images. This information would be very beneficial in a large number of applications in agriculture such as fruit picking, yield monitoring, forecasting and phenotyping. In this paper, we conducted a study on the application of modern 3D sensing technology together with the state-of-the-art machine learning algorithms for segmentation and detection of strawberries growing in real farms. We evaluate the performance of two state-of-the-art 3D sensing technologies and showcase the differences between 2D and 3D networks trained on the images and point clouds of strawberry plants and fruit. Our study highlights limitations of the current 3D vision systems for detection of small objects in outdoor applications and sets out foundations for future work on 3D perception for challenging outdoor applications such as agriculture.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Louedec, J.; Li, B. and Cielniak, G. (2020). Evaluation of 3D Vision Systems for Detection of Small Objects in Agricultural Environments. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP; ISBN 978-989-758-402-2; ISSN 2184-4321, SciTePress, pages 682-689. DOI: 10.5220/0009182806820689

@conference{visapp20,
author={Justin Le Louedec. and Bo Li. and Grzegorz Cielniak.},
title={Evaluation of 3D Vision Systems for Detection of Small Objects in Agricultural Environments},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP},
year={2020},
pages={682-689},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009182806820689},
isbn={978-989-758-402-2},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP
TI - Evaluation of 3D Vision Systems for Detection of Small Objects in Agricultural Environments
SN - 978-989-758-402-2
IS - 2184-4321
AU - Louedec, J.
AU - Li, B.
AU - Cielniak, G.
PY - 2020
SP - 682
EP - 689
DO - 10.5220/0009182806820689
PB - SciTePress

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