FieldSAFE: Dataset for Obstacle Detection in Agriculture.
Sensors (Basel)
; 17(11)2017 Nov 09.
Article
en En
| MEDLINE
| ID: mdl-29120383
In this paper, we present a multi-modal dataset for obstacle detection in agriculture. The dataset comprises approximately 2 h of raw sensor data from a tractor-mounted sensor system in a grass mowing scenario in Denmark, October 2016. Sensing modalities include stereo camera, thermal camera, web camera, 360 ∘ camera, LiDAR and radar, while precise localization is available from fused IMU and GNSS. Both static and moving obstacles are present, including humans, mannequin dolls, rocks, barrels, buildings, vehicles and vegetation. All obstacles have ground truth object labels and geographic coordinates.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Tipo de estudio:
Diagnostic_studies
Idioma:
En
Revista:
Sensors (Basel)
Año:
2017
Tipo del documento:
Article
País de afiliación:
Dinamarca