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Authors: Stefan-Daniel Suvei ; Frederik Haarslev ; Leon Bodenhagen and Norbert Krüger

Affiliation: University of Southern Denmark, Denmark

Keyword(s): Agricultural Robot, Sensor Fusion, Neural Network.

Related Ontology Subjects/Areas/Topics: Active and Robot Vision ; Applications ; Computer Vision, Visualization and Computer Graphics ; Image Formation and Preprocessing ; Motion, Tracking and Stereo Vision ; Multimodal and Multi-Sensor Models of Image Formation ; Pattern Recognition ; Robotics ; Software Engineering

Abstract: In this paper we propose a fusion method which uses the depth information acquired from a LIDAR sensor to guide a block matching stereo algorithm. The resulting fused point clouds are then used for obstacle detection, either by processing the raw data and clustering the protruding objects in the scene, or by applying a Convolutional Neural Network on the 3D points and labeling them into classes. The performance of the proposed method is evaluated by carrying out a series of experiments on different data sets obtained from the SAFE robotic platform. The results show that the fusion algorithm significantly improves the F1 detection score of the trained networks.

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Paper citation in several formats:
Suvei, S.; Haarslev, F.; Bodenhagen, L. and Krüger, N. (2018). Stereo and LIDAR Fusion based Detection of Humans and Other Obstacles in Farming Scenarios. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 4: VISAPP; ISBN 978-989-758-290-5; ISSN 2184-4321, SciTePress, pages 166-173. DOI: 10.5220/0006619801660173

@conference{visapp18,
author={Stefan{-}Daniel Suvei. and Frederik Haarslev. and Leon Bodenhagen. and Norbert Krüger.},
title={Stereo and LIDAR Fusion based Detection of Humans and Other Obstacles in Farming Scenarios},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 4: VISAPP},
year={2018},
pages={166-173},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006619801660173},
isbn={978-989-758-290-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 4: VISAPP
TI - Stereo and LIDAR Fusion based Detection of Humans and Other Obstacles in Farming Scenarios
SN - 978-989-758-290-5
IS - 2184-4321
AU - Suvei, S.
AU - Haarslev, F.
AU - Bodenhagen, L.
AU - Krüger, N.
PY - 2018
SP - 166
EP - 173
DO - 10.5220/0006619801660173
PB - SciTePress