Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry
The present dataset contains colour images acquired in a commercial Fuji apple orchard (Malus domestica Borkh. cv. Fuji) to reconstruct the 3D model of 11 trees by using structure-from-motion (SfM) photogrammetry. The data provided in this article is related to the research article entitled “Fruit d...
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| Format: | Article |
| Language: | English |
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Elsevier
2020-06-01
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| Series: | Data in Brief |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340920304856 |
| _version_ | 1811286291747176448 |
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| author | Jordi Gené-Mola Ricardo Sanz-Cortiella Joan R. Rosell-Polo Josep-Ramon Morros Javier Ruiz-Hidalgo Verónica Vilaplana Eduard Gregorio |
| author_facet | Jordi Gené-Mola Ricardo Sanz-Cortiella Joan R. Rosell-Polo Josep-Ramon Morros Javier Ruiz-Hidalgo Verónica Vilaplana Eduard Gregorio |
| author_sort | Jordi Gené-Mola |
| collection | DOAJ |
| description | The present dataset contains colour images acquired in a commercial Fuji apple orchard (Malus domestica Borkh. cv. Fuji) to reconstruct the 3D model of 11 trees by using structure-from-motion (SfM) photogrammetry. The data provided in this article is related to the research article entitled “Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry” [1]. The Fuji-SfM dataset includes: (1) a set of 288 colour images and the corresponding annotations (apples segmentation masks) for training instance segmentation neural networks such as Mask-RCNN; (2) a set of 582 images defining a motion sequence of the scene which was used to generate the 3D model of 11 Fuji apple trees containing 1455 apples by using SfM; (3) the 3D point cloud of the scanned scene with the corresponding apple positions ground truth in global coordinates. With that, this is the first dataset for fruit detection containing images acquired in a motion sequence to build the 3D model of the scanned trees with SfM and including the corresponding 2D and 3D apple location annotations. This data allows the development, training, and test of fruit detection algorithms either based on RGB images, on coloured point clouds or on the combination of both types of data. |
| first_indexed | 2024-04-13T02:57:29Z |
| format | Article |
| id | doaj.art-200301a158074038939fc3f07700f6c1 |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-04-13T02:57:29Z |
| publishDate | 2020-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-200301a158074038939fc3f07700f6c12022-12-22T03:05:34ZengElsevierData in Brief2352-34092020-06-0130105591Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetryJordi Gené-Mola0Ricardo Sanz-Cortiella1Joan R. Rosell-Polo2Josep-Ramon Morros3Javier Ruiz-Hidalgo4Verónica Vilaplana5Eduard Gregorio6Research Group in AgroICT & Precision Agriculture, Department of Agricultural and Forest Engineering, Universitat de Lleida (UdL) – Agrotecnio Center, Lleida, Catalonia, Spain; Corresponding author.Research Group in AgroICT & Precision Agriculture, Department of Agricultural and Forest Engineering, Universitat de Lleida (UdL) – Agrotecnio Center, Lleida, Catalonia, SpainResearch Group in AgroICT & Precision Agriculture, Department of Agricultural and Forest Engineering, Universitat de Lleida (UdL) – Agrotecnio Center, Lleida, Catalonia, SpainDepartment of Signal Theory and Communications, Universitat Politècnica de Catalunya, Barcelona, Catalonia, SpainDepartment of Signal Theory and Communications, Universitat Politècnica de Catalunya, Barcelona, Catalonia, SpainDepartment of Signal Theory and Communications, Universitat Politècnica de Catalunya, Barcelona, Catalonia, SpainResearch Group in AgroICT & Precision Agriculture, Department of Agricultural and Forest Engineering, Universitat de Lleida (UdL) – Agrotecnio Center, Lleida, Catalonia, SpainThe present dataset contains colour images acquired in a commercial Fuji apple orchard (Malus domestica Borkh. cv. Fuji) to reconstruct the 3D model of 11 trees by using structure-from-motion (SfM) photogrammetry. The data provided in this article is related to the research article entitled “Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry” [1]. The Fuji-SfM dataset includes: (1) a set of 288 colour images and the corresponding annotations (apples segmentation masks) for training instance segmentation neural networks such as Mask-RCNN; (2) a set of 582 images defining a motion sequence of the scene which was used to generate the 3D model of 11 Fuji apple trees containing 1455 apples by using SfM; (3) the 3D point cloud of the scanned scene with the corresponding apple positions ground truth in global coordinates. With that, this is the first dataset for fruit detection containing images acquired in a motion sequence to build the 3D model of the scanned trees with SfM and including the corresponding 2D and 3D apple location annotations. This data allows the development, training, and test of fruit detection algorithms either based on RGB images, on coloured point clouds or on the combination of both types of data.http://www.sciencedirect.com/science/article/pii/S2352340920304856Fruit detectionYield predictionYield mappingStructure-from-motionPhotogrammetryMask R-CNN |
| spellingShingle | Jordi Gené-Mola Ricardo Sanz-Cortiella Joan R. Rosell-Polo Josep-Ramon Morros Javier Ruiz-Hidalgo Verónica Vilaplana Eduard Gregorio Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry Data in Brief Fruit detection Yield prediction Yield mapping Structure-from-motion Photogrammetry Mask R-CNN |
| title | Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry |
| title_full | Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry |
| title_fullStr | Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry |
| title_full_unstemmed | Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry |
| title_short | Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry |
| title_sort | fuji sfm dataset a collection of annotated images and point clouds for fuji apple detection and location using structure from motion photogrammetry |
| topic | Fruit detection Yield prediction Yield mapping Structure-from-motion Photogrammetry Mask R-CNN |
| url | http://www.sciencedirect.com/science/article/pii/S2352340920304856 |
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