Sensors 2017, 17(11), 2579; https://doi.org/10.3390/s17112579
FieldSAFE: Dataset for Obstacle Detection in Agriculture
Mikkel Fly Kragh 1,†,*
, Peter Christiansen 1,†, Morten Stigaard Laursen 1, Morten Larsen 2, Kim Arild Steen 3, Ole Green 3, Henrik Karstoft 1 and Rasmus Nyholm Jørgensen 1
, Peter Christiansen 1,†, Morten Stigaard Laursen 1, Morten Larsen 2, Kim Arild Steen 3, Ole Green 3, Henrik Karstoft 1 and Rasmus Nyholm Jørgensen 11
Department of Engineering, Aarhus University, Aarhus N 8200, Denmark
2
Conpleks Innovation ApS, Struer 7600, Denmark
3
AgroIntelli, Aarhus N 8200, Denmark
†
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 28 September 2017 / Revised: 6 November 2017 / Accepted: 7 November 2017 / Published: 9 November 2017
(This article belongs to the Special Issue Sensors in Agriculture)
Abstract
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, 360Keywords:
dataset; agriculture; obstacle detection; computer vision; cameras; stereo imaging; thermal imaging; LiDAR; radar; object tracking
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Supplementary material
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Externally hosted supplementary file 1
Link: https://vision.eng.au.dk/fieldsafe/
Description: Website for the FieldSAFE dataset including downloads and descriptions of usage.
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MDPI and ACS Style
Kragh, M.F.; Christiansen, P.; Laursen, M.S.; Larsen, M.; Steen, K.A.; Green, O.; Karstoft, H.; Jørgensen, R.N. FieldSAFE: Dataset for Obstacle Detection in Agriculture. Sensors 2017, 17, 2579.
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