Fruit detection and 3D location using instance segmentation neural networks and SfM photogrammetry

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2020
Author
Gregorio López, Eduard
Sanz Cortiella, Ricardo
Rosell Polo, Joan Ramon
Morros Rubió, Josep Ramon
Ruiz Hidalgo, Javier
Vilaplana Besler, Verónica
Gregorio López, Eduard
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Gregorio López, Eduard; Sanz Cortiella, Ricardo; Rosell Polo, Joan Ramon; Morros Rubió, Josep Ramon; Ruiz Hidalgo, Javier; Vilaplana Besler, Verónica; Gregorio López, Eduard; . (2020) . Fruit detection and 3D location using instance segmentation neural networks and SfM photogrammetry. 7th Annual Catalan Meeting on Computer Vision. September 22, 2020, Universitat Autònoma de Barcelona, (http://acmcv.cat/). http://hdl.handle.net/10459.1/84029.
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Abstract
The 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.
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http://hdl.handle.net/10459.1/67802
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http://hdl.handle.net/10459.1/84029
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7th Annual Catalan Meeting on Computer Vision. September 22, 2020, Universitat Autònoma de Barcelona, (http://acmcv.cat/)
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