Abstract
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.
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