Browsing Comunicacions a congressos (Grup de Recerca en AgròTICa i Agricultura de Precisió) by Author "Morros Rubió, Josep Ramon"
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- ItemOpen AccessAmodal segmentation for on-tree apple fruit size es timation with RGB-D images(2023) Gené Mola, Jordi; Gregorio López, Eduard; Ferrer Ferrer , Mar; Blok, Pieter M.; Hemming, Jochen; Morros Rubió, Josep Ramon; Rosell Polo, Joan Ramon; Vilaplana Besler, Verónica; Ruiz Hidalgo, JavierThe detection and sizing of fruits with computer vision methods is of interest because it provides relevant information to improve the management of orchard farming. However, the presence of partially occluded fruits limits the performance of existing methods, making reliable fruit sizing a challenging task. While previous fruit segmentation works limit segmentation to the visible region of fruits (known as modal segmentation), in this work we propose an amodal segmentation algorithm to predict the complete shape, which includes its visible and occluded regions. CONCLUSIONS The main advantages of the present methodology are its robustness for measuring partially occluded fruits and the capability to determine the visibility percentage. Future works should evaluate the performance of the method with commercial RGB-D sensors, which would facilitate data collection.
- ItemOpen AccessFruit detection and 3D location using instance segmentation neural networks and SfM photogrammetry(2020) Gregorio López, Eduard; Sanz Cortiella, Ricardo; Rosell Polo, Joan Ramon; Morros Rubió, Josep Ramon; Ruiz Hidalgo, Javier; Vilaplana Besler, Verónica; Gregorio López, EduardThe development of remote fruit detection systems able to identify and 3D locate fruits provides opportunities to improve the effi-ciency of agriculture management. Most of the current fruit detec-tion systems are based on 2D image analysis. Although the use of 3D sensors is emerging, precise 3D fruit location is still a pending issue. This work presents a new methodology for fruit detection and 3D location, combining the use of instance segmentation neu-ral networks and Structure-from-Motion (SfM) photogrammetry.