PFuji-Size dataset: A collection of images and photogrammetry-derived 3D point clouds with ground truth annotations for Fuji apple detection and size estimation in field conditions

The PFuji-Size dataset is comprised of a collection of 3D point clouds of Fuji apple trees (Malus domestica Borkh. cv. Fuji) scanned at different maturity stages and annotated for fruit detection and size estimation. Structure-from-motion and multi-view stereo techniques were used to generate the 3D...

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Autores principales:	Jordi Gené-Mola, Ricardo Sanz-Cortiella, Joan R. Rosell-Polo, Alexandre Escolà, Eduard Gregorio
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Fruit detection Fruit size 3D object detection Structure-from-motion Multi-view stereo Agricultural robotics Computer applications to medicine. Medical informatics R858-859.7 Science (General) Q1-390
Acceso en línea:	https://doaj.org/article/678e3b1613b245f29dad68d87a4fdccc
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spelling	oai:doaj.org-article:678e3b1613b245f29dad68d87a4fdccc2021-11-28T04:33:27ZPFuji-Size dataset: A collection of images and photogrammetry-derived 3D point clouds with ground truth annotations for Fuji apple detection and size estimation in field conditions2352-340910.1016/j.dib.2021.107629https://doaj.org/article/678e3b1613b245f29dad68d87a4fdccc2021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2352340921009045https://doaj.org/toc/2352-3409The PFuji-Size dataset is comprised of a collection of 3D point clouds of Fuji apple trees (Malus domestica Borkh. cv. Fuji) scanned at different maturity stages and annotated for fruit detection and size estimation. Structure-from-motion and multi-view stereo techniques were used to generate the 3D point clouds of 6 complete Fuji apple trees containing a total of 615 apples. The resulting point clouds were 3D segmented by identifying the 3D points corresponding to each apple (3D instance segmentation), obtaining a single point cloud for each apple. All segmented apples were labelled with ground truth diameter annotations. Since the data was acquired in field conditions and at different maturity stages, the set includes different fruit diameters -from 26.9 mm to 94.8 mm- and different fruit occlusion percentages due to foliage. In addition, 25 apples were photographed 360° in laboratory conditions, obtaining high resolution 3D point clouds of this sub-set. To the best of the authors’ knowledge, this is the first publicly available dataset for apple size estimation in field conditions. This dataset was used to evaluate different fruit size estimation methods in the research article titled “In-field apple size estimation using photogrammetry-derived 3D point clouds: comparison of 4 different methods considering fruit occlusion” (Gené-Mola et al., 2021).Jordi Gené-MolaRicardo Sanz-CortiellaJoan R. Rosell-PoloAlexandre EscolàEduard GregorioElsevierarticleFruit detectionFruit size3D object detectionStructure-from-motionMulti-view stereoAgricultural roboticsComputer applications to medicine. Medical informaticsR858-859.7Science (General)Q1-390ENData in Brief, Vol 39, Iss , Pp 107629- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Fruit detection Fruit size 3D object detection Structure-from-motion Multi-view stereo Agricultural robotics Computer applications to medicine. Medical informatics R858-859.7 Science (General) Q1-390
spellingShingle	Fruit detection Fruit size 3D object detection Structure-from-motion Multi-view stereo Agricultural robotics Computer applications to medicine. Medical informatics R858-859.7 Science (General) Q1-390 Jordi Gené-Mola Ricardo Sanz-Cortiella Joan R. Rosell-Polo Alexandre Escolà Eduard Gregorio PFuji-Size dataset: A collection of images and photogrammetry-derived 3D point clouds with ground truth annotations for Fuji apple detection and size estimation in field conditions
description	The PFuji-Size dataset is comprised of a collection of 3D point clouds of Fuji apple trees (Malus domestica Borkh. cv. Fuji) scanned at different maturity stages and annotated for fruit detection and size estimation. Structure-from-motion and multi-view stereo techniques were used to generate the 3D point clouds of 6 complete Fuji apple trees containing a total of 615 apples. The resulting point clouds were 3D segmented by identifying the 3D points corresponding to each apple (3D instance segmentation), obtaining a single point cloud for each apple. All segmented apples were labelled with ground truth diameter annotations. Since the data was acquired in field conditions and at different maturity stages, the set includes different fruit diameters -from 26.9 mm to 94.8 mm- and different fruit occlusion percentages due to foliage. In addition, 25 apples were photographed 360° in laboratory conditions, obtaining high resolution 3D point clouds of this sub-set. To the best of the authors’ knowledge, this is the first publicly available dataset for apple size estimation in field conditions. This dataset was used to evaluate different fruit size estimation methods in the research article titled “In-field apple size estimation using photogrammetry-derived 3D point clouds: comparison of 4 different methods considering fruit occlusion” (Gené-Mola et al., 2021).
format	article
author	Jordi Gené-Mola Ricardo Sanz-Cortiella Joan R. Rosell-Polo Alexandre Escolà Eduard Gregorio
author_facet	Jordi Gené-Mola Ricardo Sanz-Cortiella Joan R. Rosell-Polo Alexandre Escolà Eduard Gregorio
author_sort	Jordi Gené-Mola
title	PFuji-Size dataset: A collection of images and photogrammetry-derived 3D point clouds with ground truth annotations for Fuji apple detection and size estimation in field conditions
title_short	PFuji-Size dataset: A collection of images and photogrammetry-derived 3D point clouds with ground truth annotations for Fuji apple detection and size estimation in field conditions
title_full	PFuji-Size dataset: A collection of images and photogrammetry-derived 3D point clouds with ground truth annotations for Fuji apple detection and size estimation in field conditions
title_fullStr	PFuji-Size dataset: A collection of images and photogrammetry-derived 3D point clouds with ground truth annotations for Fuji apple detection and size estimation in field conditions
title_full_unstemmed	PFuji-Size dataset: A collection of images and photogrammetry-derived 3D point clouds with ground truth annotations for Fuji apple detection and size estimation in field conditions
title_sort	pfuji-size dataset: a collection of images and photogrammetry-derived 3d point clouds with ground truth annotations for fuji apple detection and size estimation in field conditions
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/678e3b1613b245f29dad68d87a4fdccc
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PFuji-Size dataset: A collection of images and photogrammetry-derived 3D point clouds with ground truth annotations for Fuji apple detection and size estimation in field conditions

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