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Authors: Belén Luque ; Josep Ramon Morros and Javier Ruiz-Hidalgo

Affiliation: Universitat Politècnica de Catalunya - BarcelonaTech, Spain

Keyword(s): Computer Vision, Road Detection, Segmentation, Drones, Neural Networks, CNNs.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Segmentation and Grouping

Abstract: The main goal of this paper is to detect roads from aerial imagery recorded by drones. To achieve this, we propose a modification of SegNet, a deep fully convolutional neural network for image segmentation. In order to train this neural network, we have put together a database containing videos of roads from the point of view of a small commercial drone. Additionally, we have developed an image annotation tool based on the watershed technique, in order to perform a semi-automatic labeling of the videos in this database. The experimental results using our modified version of SegNet show a big improvement on the performance of the neural network when using aerial imagery, obtaining over 90% accuracy.

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Paper citation in several formats:
Luque, B.; Morros, J. and Ruiz-Hidalgo, J. (2017). Spatio-temporal Road Detection from Aerial Imagery using CNNs. In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP; ISBN 978-989-758-225-7; ISSN 2184-4321, SciTePress, pages 493-500. DOI: 10.5220/0006128904930500

@conference{visapp17,
author={Belén Luque. and Josep Ramon Morros. and Javier Ruiz{-}Hidalgo.},
title={Spatio-temporal Road Detection from Aerial Imagery using CNNs},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP},
year={2017},
pages={493-500},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006128904930500},
isbn={978-989-758-225-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP
TI - Spatio-temporal Road Detection from Aerial Imagery using CNNs
SN - 978-989-758-225-7
IS - 2184-4321
AU - Luque, B.
AU - Morros, J.
AU - Ruiz-Hidalgo, J.
PY - 2017
SP - 493
EP - 500
DO - 10.5220/0006128904930500
PB - SciTePress