Face detection by aggregated Bayesian network classifiers
Pattern Recognition Letters - In memory of Professor E.S. Gelsema
Statistical Learning of Multi-view Face Detection
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Face Detection Using Mixtures of Linear Subspaces
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Object Detection Using the Statistics of Parts
International Journal of Computer Vision
FloatBoost Learning and Statistical Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian discriminating features method for face detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
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The face images are varying environment database from external illumination. Therefore we propose parallel cascade face detector. We define context image illumination and distinguish context using unsupervised learning. Many unsupervised method is available to distinguish varying illuminant images. This approach can be distribution face image and we can make the classifier for face image context. Therefore, in this paper, we parallel classifier that is strutted cascade classifier of two methods. In first classifier, we use sub-sampling feature extraction and in second classifier we use wavelet transformation method. We achieved very encouraging experimental results. Our method is enhancement varying illumination environment.