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Authors: Tien-Wen Yeh 1 and Huei-Yung Lin 2

Affiliations: 1 Department of Electrical Engineering, National Chung Cheng University, Chiayi 621, Taiwan ; 2 Department of Electrical Engineering and Advanced Institute of Manufacturing with High-tech Innovations National Chung Cheng University, Chiayi 621, Taiwan

Keyword(s): Traffic Light Detection, Traffic Light Recognition, Arrow Traffic Signal.

Abstract: This paper develops a traffic light detection and recognition system based on convolutional neural networks for Taiwan road scenes. A two-stage approach is proposed with first detecting the traffic light position, followed by the light state recognition. It is specifically designed to identify the challenging arrow signal lights in many urban traffic scenes. In the detection stage, the map information and two cameras with different focal lengths are used to detect the traffic lights at different distances. In the recognition stage, a new method combining object detection and classification is proposed to deal with various light state classes in Taiwan road scenes. Furthermore, an end-to-end network with shared feature maps is implemented to reduce the computation time. Experiments are carried out on the public LISA dataset and our own dataset collected from two routes with urban traffic scenes.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Yeh, T. and Lin, H. (2020). Detection and Recognition of Arrow Traffic Signals using a Two-stage Neural Network Structure. In Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS; ISBN 978-989-758-419-0; ISSN 2184-495X, SciTePress, pages 322-330. DOI: 10.5220/0009345203220330

@conference{vehits20,
author={Tien{-}Wen Yeh. and Huei{-}Yung Lin.},
title={Detection and Recognition of Arrow Traffic Signals using a Two-stage Neural Network Structure},
booktitle={Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS},
year={2020},
pages={322-330},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009345203220330},
isbn={978-989-758-419-0},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS
TI - Detection and Recognition of Arrow Traffic Signals using a Two-stage Neural Network Structure
SN - 978-989-758-419-0
IS - 2184-495X
AU - Yeh, T.
AU - Lin, H.
PY - 2020
SP - 322
EP - 330
DO - 10.5220/0009345203220330
PB - SciTePress