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Authors: Mohsen Shirpour ; Steven S. Beauchemin and Michael A. Bauer

Affiliation: Department of Computer Science, The University of Western Ontario, London, ON, N6A-5B7, Canada

Keyword(s): Driver’s Eye Fixation, Saliency Region, Convolution Neural Network, Eye Tracking, Traffic Driving.

Abstract: The driving environment is a complex dynamic scene in which a driver’s eye fixation interacts with traffic scene objects to protect the driver from dangerous situations. Prediction of a driver’s eye fixation plays a crucial role in Advanced Driving Assistance Systems (ADAS) and autonomous vehicles. However, currently, no computational framework has been introduced to combine the bottom-up saliency map with the driver’s head pose and gaze direction to estimate a driver’s eye fixation. In this work, we first propose convolution neural networks to predict the potential saliency regions in the driving environment, and then use the probability of the driver gaze direction, given head pose as a top-down factor. We evaluate our model on real data gathered during drives in an urban and suburban environment with an experimental vehicle. Our analyses show promising results.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Shirpour, M.; Beauchemin, S. and Bauer, M. (2021). Driver’s Eye Fixation Prediction by Deep Neural Network. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP; ISBN 978-989-758-488-6; ISSN 2184-4321, SciTePress, pages 67-75. DOI: 10.5220/0010220800670075

@conference{visapp21,
author={Mohsen Shirpour. and Steven S. Beauchemin. and Michael A. Bauer.},
title={Driver’s Eye Fixation Prediction by Deep Neural Network},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP},
year={2021},
pages={67-75},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010220800670075},
isbn={978-989-758-488-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP
TI - Driver’s Eye Fixation Prediction by Deep Neural Network
SN - 978-989-758-488-6
IS - 2184-4321
AU - Shirpour, M.
AU - Beauchemin, S.
AU - Bauer, M.
PY - 2021
SP - 67
EP - 75
DO - 10.5220/0010220800670075
PB - SciTePress

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