Eye Detection in Facial Images With Unconstrained Background

This paper presents an efficient eye detection approach for still, grey-level images with unconstrained background. The structure of the eye region is used as a robust cue to find eye pair candidates in the entire image. Eye pairs are located by a support vector machine-based eye verifier. The eye variance filter is then used to detect two eyes in the eye region which has been extracted in the eye pair location step. The proposed method is robust against clustered background, moderate rotations, glasses wearing, and partial face occlusions. The method is evaluated using the BioID face database. The experimental results demonstrate the effectiveness of the presented method.

[1]  Federico Girosi,et al.  Training support vector machines: an application to face detection , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[2]  A. Oppenheim,et al.  Nonlinear filtering of multiplied and convolved signals , 1968 .

[3]  Mohamed Rizon,et al.  Iris detection using intensity and edge information , 2003, Pattern Recognit..

[4]  Tomaso A. Poggio,et al.  Example-Based Learning for View-Based Human Face Detection , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Chin-Chuan Han,et al.  Fast face detection via morphology-based pre-processing , 2000, Pattern Recognit..

[6]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[7]  Paola Campadelli.  LOCALIZATION OF FACIAL FEATURES AND FIDUCIAL POINTS , 2002 .

[8]  Jianxin Wu,et al.  Efficient face candidates selector for face detection , 2003, Pattern Recognit..

[9]  Tiziana D'Orazio,et al.  An algorithm for real time eye detection in face images , 2004, ICPR 2004.

[10]  Tiziana D'Orazio,et al.  An algorithm for real time eye detection in face images , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[11]  Pong C. Yuen,et al.  Multi-cues eye detection on gray intensity image , 2001, Pattern Recognit..

[12]  Volkan Atalay,et al.  Projection based method for segmentation of human face and its evaluation , 2002, Pattern Recognit. Lett..

[13]  Xiuwen Liu,et al.  Face detection using spectral histograms and SVMs , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[14]  Azriel Rosenfeld,et al.  A method of detecting and tracking irises and eyelids in video , 2002, Pattern Recognit..

[15]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.

[16]  Irfan A. Essa,et al.  Detecting and tracking eyes by using their physiological properties, dynamics, and appearance , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).