Stereo and LIDAR Fusion based Detection of Humans and Other Obstacles in Farming Scenarios

Stefan-Daniel Suvei, Frederik Haarslev, Leon Bodenhagen, Norbert Krüger

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 Harvard Style

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 - Volume 4: VISAPP, ISBN 978-989-758-290-5, pages 166-173. DOI: 10.5220/0006619801660173


in Bibtex Style

@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 - Volume 4: VISAPP,},
year={2018},
pages={166-173},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006619801660173},
isbn={978-989-758-290-5},
}


in EndNote Style

TY - CONF

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