IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition: Features Versus Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition from a single image per person: A survey
Pattern Recognition
Face detection with the modified census transform
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Face recognition: a convolutional neural-network approach
IEEE Transactions on Neural Networks
Facial fraud discrimination using detection and classification
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part III
Hi-index | 0.00 |
This paper proposes a novel eye detection method using the MCT-based pattern correlation. The proposed method detects the face by the MCT-based AdaBoost face detector over the input image and then detects two eyes by the MCT-based AdaBoost eye detector over the eye regions. Sometimes, we have some incorrectly detected eyes due to the limited detection capability of the eye detector. To reduce the falsely detected eyes, we propose a novel eye verification method that employs the MCT-based pattern correlation map. We verify whether the detected eye patch is eye or non-eye depending on the existence of a noticeable peak. When one eye is correctly detected and the other eye is falsely detected, we can correct the falsely detected eye using the peak position of the correlation map of the correctly detected eye. Experimental results show that the eye detection rate of the proposed method is 98.7% and 98.8% on the Bern images and AR-564 images.