Chenjian Wu

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AdaBoost algorithm based on Haar-like features can achieves high accuracy (above 95%) in object detection. Meanwhile massive computing power is needed to implement the cascaded classifiers involved in AdaBoost detection. To solve this problem, several dedicated hardware solutions have been proposed for real-time applications. In this work, a novel(More)
In this paper, the cross-database facial expression recognition problem is studied. First, Gaussian Mixture Model is used to improve the facial landmark detection. Second, the local image features are used to model the facial actions. Deep Neural Network is used to represent the low level data variance. Third, the top level expression recognition rules are(More)
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