SESAM: A Biometric Person Identification System Using Sensor Fusion
AVBPA '97 Proceedings of the First International Conference on Audio- and Video-Based Biometric Person Authentication
Face Pose Discrimination Using Support Vector Machines (SVM)
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Facial Component Extraction and Face Recognition with Support Vector Machines
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Robust Real-Time Face Detection
International Journal of Computer Vision
Learn Discriminant Features for Multi-View Face and Eye Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Adaptive Smoothing via Contextual and Local Discontinuities
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
Computer Vision and Image Understanding - Special issue on eye detection and tracking
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Face recognition under varying lighting conditions using self quotient image
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Real-time visual content description system based on MPEG-7 descriptors
Multimedia Tools and Applications
Properties and performance of a center/surround retinex
IEEE Transactions on Image Processing
A multiscale retinex for bridging the gap between color images and the human observation of scenes
IEEE Transactions on Image Processing
Accurate Eye Center Location through Invariant Isocentric Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Illumination invariant eye detection in facial images based on the retinex theory
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
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Eye detection plays an important role in face recognition because eyes provide distinctive facial features. However, illumination effects such as heavy shadows and drastic lighting change make it difficult to detect eyes well in facial images. In this paper, we propose a novel framework for illumination invariant eye detection under varying lighting conditions. First, we use adaptive smoothing based on the retinex theory to remove the illumination effects. Second, we perform eye candidate detection using the edge histogram descriptor (EHD) on the illumination normalized-facial images. Third, we employ the support vector machine (SVM) classification for eye verification. Finally, we determine eye positions using eye probability map (EPM). Experimental results on the CMU-PIE, Yale B, and AR face databases demonstrate that the proposed method achieves high detection accuracy and fast computation speed in eye detection.