Image Representation Using 2D Gabor Wavelets
IEEE Transactions on Pattern Analysis and Machine Intelligence
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Face Detection Using the Hausdorff Distance
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Robust Real-Time Face Detection
International Journal of Computer Vision
An Algorithm for Real Time Eye Detection in Face Images
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
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
Face Description with Local Binary Patterns: Application to Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Editorial: Special issue: eye detection and tracking
Computer Vision and Image Understanding - Special issue on eye detection and tracking
Locating and extracting the eye in human face images
Pattern Recognition
Robust precise eye location by adaboost and SVM techniques
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Independent component analysis of Gabor features for face recognition
IEEE Transactions on Neural Networks
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The eye localization is a fundamental step in human-computer interaction and automatic face recognition. In this paper, a new eye detection method for face images is proposed. Firstly, the rough eye positions are found by Gabor transformation and cluster analysis. Secondly, a detection of pupil centers will be continued by applying two neighborhood operators in the rough eye regions. A subset of the color FERET database and the Faces 1999 database are used to evaluate the proposed method. Results of experiments show that our method is robust and efficient.