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Fuji-SfM dataset Computer Vision Project

Images

288 images
Explore Dataset

This is part (1) of the Fuji-SfM dataset. 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 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. 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.

Methodology

The reader is referred to visit articles [1] and [2] for a description of methodology and further information about this dataset.

Aknowledgements

This work was partly funded by the Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya (grant 2017 SGR 646), the Spanish Ministry of Economy and Competitiveness (project AGL2013-48297-C2-2-R) and the Spanish Ministry of Science, Innovation and Universities (project RTI2018-094222-B-I00). Part of the work was also developed within the framework of the project TEC2016-75976-R, financed by the Spanish Ministry of Economy, Industry and Competitiveness and the European Regional Development Fund (ERDF). The Spanish Ministry of Education is thanked for Mr. J. Gené’s pre-doctoral fellowships (FPU15/03355). We would also like to thank Nufri (especially Santiago Salamero and Oriol Morreres) and Vicens Maquinària Agrícola S.A. for their support during data acquisition, and Ernesto Membrillo and Roberto Maturino for their support in dataset labelling.

License

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License (CC-BY-NC-SA)

This database is available only for research and educational purpose and not for any commercial use. If you use the database in any publications or reports, you must refer to the following papers:

[1] Gené-Mola J, Sanz-Cortiella R, Rosell-Polo JR, Morros J-R, Ruiz-Hidalgo J, Vilaplana V, , Gregorio E. 2020. Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry. Computers and Electronics in Agriculture, 169 (2020), 105165. DOI: 10.1016/j.compag.2019.105165

[2] Gené-Mola J, Sanz-Cortiella R, Rosell-Polo JR, Morros J-R, Ruiz-Hidalgo J, Vilaplana V, , Gregorio E. 2020. Fuji-SfM dataset: a collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry. (Submitted)

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            fuji-sfm-dataset_dataset,
                            title = { Fuji-SfM dataset Dataset },
                            type = { Open Source Dataset },
                            author = { new-workspace-txyl7 },
                            howpublished = { \url{ https://universe.roboflow.com/new-workspace-txyl7/fuji-sfm-dataset } },
                            url = { https://universe.roboflow.com/new-workspace-txyl7/fuji-sfm-dataset },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2021 },
                            month = { dec },
                            note = { visited on 2024-07-19 },
                            }
                        

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Last Updated

3 years ago

Project Type

Object Detection

Subject

apple

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License

BY-NC-SA 4.0

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