Dense Semantic Stereo Labelling Architecture for In-Campus Navigation

Jorge Beltrán, Carlos Jaraquemada, Basam Musleh, Arturo De La Escalera, Jose María Armingol

Abstract

Interest on autonomous vehicles has rapidly increased in the last few years, due to recent advances in the field and the appearance of semi-autonomous solutions in the market. In order to reach fully autonomous navigation, a precise understanding of the vehicle surroundings is required. This paper presents a novel ROS-based architecture for stereo-vision-based semantic scene labelling. The objective is to provide the necessary information to a path planner in order to perform autonomous navigation around the university campus. The output of the algorithm contains the classification of the obstacles in the scene into four different categories: traversable areas, garden, static obstacles, and pedestrians. Validation of the labelling method is accomplished by means of a hand-labelled ground truth, generated from a stereo sequence captured in the university campus. The experimental results show the high performance of the proposed approach.

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Paper Citation


in Harvard Style

Beltrán J., Jaraquemada C., Musleh B., De La Escalera A. and Armingol J. (2017). Dense Semantic Stereo Labelling Architecture for In-Campus Navigation . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-226-4, pages 266-273. DOI: 10.5220/0006131602660273


in Bibtex Style

@conference{visapp17,
author={Jorge Beltrán and Carlos Jaraquemada and Basam Musleh and Arturo De La Escalera and Jose María Armingol},
title={Dense Semantic Stereo Labelling Architecture for In-Campus Navigation},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={266-273},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006131602660273},
isbn={978-989-758-226-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017)
TI - Dense Semantic Stereo Labelling Architecture for In-Campus Navigation
SN - 978-989-758-226-4
AU - Beltrán J.
AU - Jaraquemada C.
AU - Musleh B.
AU - De La Escalera A.
AU - Armingol J.
PY - 2017
SP - 266
EP - 273
DO - 10.5220/0006131602660273