Head pose and eye location estimation are two closely
related issues which refer to similar application areas. In
recent years, these problems have been studied individually
in numerous works in the literature. Previous research
shows that cylindrical head models and isophote based
schemes provide satisfactory precision in head pose and eye
location estimation, respectively. However, the eye locator
is not adequate to accurately locate eye in the presence
of extreme head poses. Therefore, head pose cues may be
suited to enhance the accuracy of eye localization in the
presence of severe head poses.
In this paper, a hybrid scheme is proposed in which the
transformation matrix obtained from the head pose is used
to normalize the eye regions and, in turn the transformation
matrix generated by the found eye location is used to
correct the pose estimation procedure. The scheme is designed
to (1) enhance the accuracy of eye location estimations
in low resolution videos, (2) to extend the operating
range of the eye locator and (3) to improve the accuracy
and re-initialization capabilities of the pose tracker.
From the experimental results it can be derived that the
proposed unified scheme improves the accuracy of eye estimations
by 16% to 23%. Further, it considerably extends
its operating range by more than 15 degrees, by overcoming the
problems introduced by extreme head poses. Finally, the
accuracy of the head pose tracker is improved by 12% to
24%.
@InProceedings{ValentiCVPR2009,
author = "Valenti, R. and Yucel, Z. and Gevers, T.",
title = "Robustifying Eye Center Localization by Head Pose Cues",
booktitle = "IEEE Conference on Computer Vision and Pattern Recognition",
year = "2009",
url = "https://ivi.fnwi.uva.nl/isis/publications/2009/ValentiCVPR2009",
pdf = "https://ivi.fnwi.uva.nl/isis/publications/2009/ValentiCVPR2009/ValentiCVPR2009.pdf",
has_image = 1
}