Eye Detection with Faster R-CNN

Jiali Cui, Fuqiang Chen, Duo Shi, Liqiang Liu

2019

Abstract

The accuracy of eye detection is crucial to a variety of biometric identification technologies, such as iris recognition. The challenge of eye detection comes from improving accuracy of detection in the case of occlusion or reflection of glasses. In this paper, an eye detection method based on Faster Region-based Convolutional Neural Network (Faster R-CNN) is proposed. The method includes three import parts: convolutional layers, region proposal network (RPN) and detection network. By training monocular and binocular models on the training dataset, the recall of monocular and binocular models on test dataset can reach 96% and 95% respectively, which proves that the proposed method based on Faster R-CNN has high accuracy of detection in the task.

Paper Citation

in Harvard Style

Cui J., Chen F., Shi D. and Liu L. (2019). Eye Detection with Faster R-CNN.In Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - Volume 1: CTISC, ISBN 978-989-758-357-5, pages 111-116. DOI: 10.5220/0008096201110116

in Bibtex Style

@conference{ctisc19,
author={Jiali Cui and Fuqiang Chen and Duo Shi and Liqiang Liu},
title={Eye Detection with Faster R-CNN},
booktitle={Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - Volume 1: CTISC,},
year={2019},
pages={111-116},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008096201110116},
isbn={978-989-758-357-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications - Volume 1: CTISC,
TI - Eye Detection with Faster R-CNN
SN - 978-989-758-357-5
AU - Cui J.
AU - Chen F.
AU - Shi D.
AU - Liu L.
PY - 2019
SP - 111
EP - 116
DO - 10.5220/0008096201110116