Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Line Edge Map
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
Improved facial-feature detection for AVSP via unsupervised clustering and discriminant analysis
EURASIP Journal on Applied Signal Processing
Robust precise eye location under probabilistic framework
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
A Bayesian discriminating features method for face detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Image Processing
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Based on template facial features and image segmentation, this paper demonstrates a novel method for automatic detection of eyes in grayscale still images. A decision model of eye location is instituted by the priori knowledge of template facial features. After roughly detection of face, we apply three steps for system to locate eyes. Firstly, the Bayesian eye detector is used to find eye patterns in the upper region of the face image. This vector based Bayesian classifier adopts Haar transform as vectorize because we know that is robust at illumination variation. Secondly, merging and arbitration strategy are applied. It can manage variations of around eye regions due to spectacle rims or eye brows. Finally, Gaussian-projection function can locate robust precision eye position. The experimental results show that the proposed method can achieve higher performance at any test data.