Facial expression recognition using joint multi-resolution multi-area ULBP representation
2010
In this paper, we propose a robust multi-layer texture representation for facial expressions. Our representation is built up
using multi-resolution (MR) uniform local binary pattern (ULBP) features on multi-areas (MA) in facial image.
Experiments show that this multi-resolution and multi-area (MRMA) strategy could both greatly improve the
discriminative ability of texture representation. Based on the proposed MRMA ULBP representation for facial expression,
we propose a MRMA ULBP representation + SVM classifier facial expression recognition system. Experiments based on
21 trained one-against-one SVM classifiers show average recognition accuracy of 92.59% on JAFFE database.
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