Pupil localization for gaze estimation using unsupervised graph-based model
Salah Rabba, Yifeng He, Matthew J. Kyan, Ling Guan · 2017
In this paper, we propose a graph-based model for pupil localization, which is a step towards gaze detection. The proposed model can differentiate the key points located at the eyelashes, eyebrows and eye white regions. We first crop the eye region with an ellipse and then estimate the pupil center within the ellipse, thus reducing the computational complexity. We also consider the light reflections in the pupil region, which could lead to inaccuracy in pupil localization. We construct an undirected graph in the eye region based on the key points consisting of the corner points in the eye region, the centers of light reflection regions, and the multiple pixels with a high intensity in the pupil region. The pupil center is initially estimated as the weighted center of the revised graph after vertex/edge removal. In addition, we shift the initial pupil center to a revised position based on the line segments in the pupil region. We evaluate the proposed method on 850 eye images from a public database. The experimental results demonstrate that the proposed method can achieve a more accurate result compared to the existing work.