Face detection by aggregated Bayesian network classifiers
Pattern Recognition Letters - In memory of Professor E.S. Gelsema
Projection based method for segmentation of human face and its evaluation
Pattern Recognition Letters
Monitoring Head/Eye Motion for Driver Alertness with One Camera
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Improved facial-feature detection for AVSP via unsupervised clustering and discriminant analysis
EURASIP Journal on Applied Signal Processing
Human face detection using skin color context awareness and context-based bayesian classifiers
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
An efficient face location using integrated feature space
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
A Bayesian discriminating features method for face detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
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In this paper, we propose the efficient face and eye detection system using context based detector. The face detection system architecture use cascade method by illuminant face model. Also, we detect eye region after face detection. We construct nine classes to eye detector. It is enhanced eye detection ratio for varying illuminant face images. We define context to illumination class and distinguish class back propagation. Also, we made in context model using face illuminant. The multiple classifiers consist of face illuminant information. Context based Bayesian classifiers are employed for selection of face and eye detection windows. Face detection system is enhanced for face detection form multiple face class and non-face class. Proposed method is high performance more than single classifier.