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A multi-level classification approach for facial emotion recognition

机译:面部情感识别的多层次分类方法

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摘要

Recognition of facial expressions and infer emotions from them is become increasingly relevant in many commercial and law enforcement applications. In this paper, we present a multi-level classification approach for human emotion recognition from facial images. In the proposed approach, the classification accuracy of principal component analysis (PCA) at level 1 is boosted by Support Vector Machines (SVMs) at level 2. Experimental results demonstrate that the proposed approach can successfully recognize facial emotion with 94% recognition rate.
机译:在许多商业和执法应用中,识别面部表情并从中推断出情感变得越来越重要。在本文中,我们提出了一种用于从面部图像识别人类情绪的多级分类方法。在该方法中,通过2级支持向量机(SVM)提高了1级主成分分析(PCA)的分类准确性。实验结果表明,该方法可以成功识别94%的面部表情。

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