Expression Detection Based on a Novel Emotion Recognition Method

As facial expression is an essential way to convey human's feelings, in this paper, a dynamic selection ensemble learning method is proposed to analyze their emotion automatically. A feature selection algorithm is proposed at first based on rough set and the domain oriented data driven data mining theory, which can get multiple reducts and candidate classifiers. Then the nearest neighborhood of each unseen sample is found in a validation subset and the most accurate classifier is extracted from the candidate classifiers. Finally, the selected classifier is used to recognize unseen samples. Experimental results show that the proposed method is effective and suitable for emotion recognition.

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