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 defining a motion sequence of the scene which was used to generate the 3D model of...
| Autores: | , , , , , , |
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| Formato: | otro |
| Fecha de publicación: | 2020 |
| País: | España |
| Recursos: | Universitat de Lleida (UdL) |
| Repositorio: | Repositori Obert UdL |
| OAI Identifier: | oai:repositori.udl.cat:10459.1/68505 |
| Acesso em linha: | http://doi.org/10.5281/zenodo.3712808 https://doi.org/10.5281/zenodo.3712808 http://hdl.handle.net/10459.1/68505 |
| Access Level: | acceso abierto |
| Palavra-chave: | Fruit detection Structure-from-motion (SfM) Photogrammetry Terrestrial remote sensing Agrobotics Yield Prediction Yield Mapping Artificial Intelligence Computer Vision Instanse segmentation Deep Learning |
| Resumo: | 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. 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. |
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