Variance projection function and its application to eye detection for human face recognition
Pattern Recognition Letters
Integrating active face tracking with model based coding
Pattern Recognition Letters
Face Recognition: Features Versus Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Eye Detection and Its Validation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
A robust method for eye features extraction on color image
Pattern Recognition Letters
Extraction and tracking of the eyelids
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04
An Effective Method for Eye Detection Based on Texture Information
ICCIT '07 Proceedings of the 2007 International Conference on Convergence Information Technology
Bosphorus Database for 3D Face Analysis
Biometrics and Identity Management
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Eye features are one of the most important clues for many computer vision applications. In this paper, an efficient method to automatically extract eye features is presented. The extraction is highly based on the usage of the common knowledge about face and eye structure. With the assumption of frontal face images, firstly coarse eye regions are extracted by removing skin pixels in the upper part of the face. Then, iris circle position and radius are detected by using Hough transform in a coarse-to-fine fashion. In the final step, edges created by upper and lower eyelids are detected and polynomials are fitted to those edges so that their intersection points are labeled as eye corners. The algorithm is experimented on the Bosphorus database and the obtained results demonstrate that it can locate eye features very accurately. The strength of the proposed method stems from its reproducibility due to the utilization of simple and efficient image processing methods while achieving remarkable results without any need of training.