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http://dx.doi.org/10.4218/etrij.13.2013.0054

Hybrid Facial Representations for Emotion Recognition  

Yun, Woo-Han (IT Convergence Technology Research Laboratory, ETRI)
Kim, DoHyung (IT Convergence Technology Research Laboratory, ETRI)
Park, Chankyu (IT Convergence Technology Research Laboratory, ETRI)
Kim, Jaehong (IT Convergence Technology Research Laboratory, ETRI)
Publication Information
ETRI Journal / v.35, no.6, 2013 , pp. 1021-1028 More about this Journal
Abstract
Automatic facial expression recognition is a widely studied problem in computer vision and human-robot interaction. There has been a range of studies for representing facial descriptors for facial expression recognition. Some prominent descriptors were presented in the first facial expression recognition and analysis challenge (FERA2011). In that competition, the Local Gabor Binary Pattern Histogram Sequence descriptor showed the most powerful description capability. In this paper, we introduce hybrid facial representations for facial expression recognition, which have more powerful description capability with lower dimensionality. Our descriptors consist of a block-based descriptor and a pixel-based descriptor. The block-based descriptor represents the micro-orientation and micro-geometric structure information. The pixel-based descriptor represents texture information. We validate our descriptors on two public databases, and the results show that our descriptors perform well with a relatively low dimensionality.
Keywords
Facial expression recognition; Histograms of Oriented Gradients, HOG; Local Binary Pattern, LBP; Rotated Local Binary Pattern, RLBP; Gabor filter, GF;
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