Eye center localization and detection using radial mapping
Karan Ahuja, Ruchika Banarjee, Seema Nagar, Kuntal Dey, Ferdous Barbhuiya
Abstract
We propose a geometrical method, applied over eye-specific features, to improve the accuracy of the art of eye-center localization. Our solution is built upon: (a) checking radially constrained gradient vectors, (b) adding weightage to iris specific features and (c) considering bi-directional image gradients to eliminate errors due to reflection on pupil. Our system outperforms the state of the art methods, when compared collectively across multiple benchmark databases, such as BioID and FERET. Our process is lightweight, robust and significantly fast: achieving 50-60 fps for eye center localization, using a single threaded approach on a 2.4 GHz CPU with no GPU. This makes it practicable for real-life applications.
Citation
Ahuja, K., Banerjee, R., Nagar, S., Dey, K., & Barbhuiya, F. (2016, September). Eye center localization and detection using radial mapping. In 2016 IEEE International Conference on image processing (ICIP) (pp. 3121-3125). IEEE.
BibTeX
@inproceedings{ahuja2016eye,
title={Eye center localization and detection using radial mapping},
author={Ahuja, Karan and Banerjee, Ruchika and Nagar, Seema and Dey, Kuntal and Barbhuiya, Ferdous},
booktitle={2016 IEEE International Conference on image processing (ICIP)},
pages={3121--3125},
year={2016},
organization={IEEE}
}