This dataset is made of natural images acquired in-field by the Intel RealSense R200 (Santa Clara, CA, USA) RGB-D camera. The resolution of the color images has been set to 640×480 pixels as the maximum achievable resolution of the depth maps (not included in this dataset). The Intel RealSense R200 is on a mobile platform (Niko caterpillar, Bühl/Baden, Germany), guided in a commercial vineyard of a white variety of wine grape (Räuschling) in Switzerland (N47°14’27.6”, E8°48’25.2”). Datasets were completed in two days of acquisitions, during which the vehicle followed specific paths within the parallel rows of grapes (row spacing between 1.5 and 2 m) at an average speed of 1.5 m/s. The camera pointed laterally at the rows of grapevines at a distance in the range between 0.75 and 1 m, producing video streams at a framerate of 5 fps. Among the whole set of images, 85 were manually annotated for semantic segmentation.

S3CavVineyardDataset

Milella A.
;
Marani R.;Petitti A.;
2019

Abstract

This dataset is made of natural images acquired in-field by the Intel RealSense R200 (Santa Clara, CA, USA) RGB-D camera. The resolution of the color images has been set to 640×480 pixels as the maximum achievable resolution of the depth maps (not included in this dataset). The Intel RealSense R200 is on a mobile platform (Niko caterpillar, Bühl/Baden, Germany), guided in a commercial vineyard of a white variety of wine grape (Räuschling) in Switzerland (N47°14’27.6”, E8°48’25.2”). Datasets were completed in two days of acquisitions, during which the vehicle followed specific paths within the parallel rows of grapes (row spacing between 1.5 and 2 m) at an average speed of 1.5 m/s. The camera pointed laterally at the rows of grapevines at a distance in the range between 0.75 and 1 m, producing video streams at a framerate of 5 fps. Among the whole set of images, 85 were manually annotated for semantic segmentation.
2019
Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato - STIIMA (ex ITIA) Sede Secondaria Bari
vineyard image segmentation; rgb-d sensing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/542143
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