Computer Science Today: Recent Trends and Developments
Computer Science Today: Recent Trends and Developments
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
Improved facial-feature detection for AVSP via unsupervised clustering and discriminant analysis
EURASIP Journal on Applied Signal Processing
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 multi-class classifier and knowledge based face detection. Eye region and face location is used illuminant based Bayesian detector. We propose the efficient face and eye detection system using varying illuminant context modeling and multi–classifier. The face detection system architecture use cascade method by illuminant face model. Also, we detect eye region after face detection. Proposed eye detection frame is multiple illuminant Bayesian classifiers. Because face images have varying illuminant and this is vary difficult problem in face detection. Therefore, we made in context model using face illuminant. The multiple classifiers consist of face illuminant information. Multiple Bayesian classifiers are employed for selection of face and eye detection windows on illuminant face group. Finally, face and eye regions of the detected candidates are selected by context awareness.