This paper proposes a novel method for localizing the center of pupils. Given a face detected in an image, it first empirically initializes the eye regions in the face, and locates the pupils within the eye regions by using an improved isophote curvature based method. It then updates the eye regions according to the detected pupil centers. In the updated eye regions, the pupil centers are also refined. The above process iterates until the detected pupil centers have sufficiently high consistency with the eye regions. Compared with previous methods, the proposed method can better cope with faces with varying pose angles. Evaluation experiments have been done on the public BioID database and a set of self-collected face images which display various pose angles and illumination conditions. The results demonstrate that the proposed method can more accurately locate pupil centers and is robust to illumination and pose variations.
CITATION STYLE
Zhu, R., Sang, G., Gao, W., & Zhao, Q. (2014). A novel iterative approach to pupil localization. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8833, 155–162. https://doi.org/10.1007/978-3-319-12484-1_17
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