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Facial expression recognition has important practical applications. In this paper, we propose a method based on the combination of optical flow and a deep neural network—stacked sparse autoencoder (SAE). This method classifies facial expressions into six categories (i.e. happiness, sadness, anger, fear, disgust and surprise). In order to extract the representation of facial expressions, we choose...
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