Facial Expression Recognition Based on Salient Regions

Facial expression recognition has been applied in many fields such as human computer interaction, patient monitoring, neurology, social robot… Although facial expression recognition has gained some encourage results, there are still many challenges such as the change of illumination, blur, etc. Especially, recognizing between sadness and anger expression raises more barriers. In this paper, we proposed a framework using only salient facial regions, but it would be able to improve the accuracy of facial expression recognition. In this framework, one of the most state-of-the-art descriptor, called Pyramid of Local Phase Quantization descriptor (PLPQ) was used to robust with respect to image blur. The experiment achieved 97.7% accuracy recognition rate on the extend Cohn-Canade (CK+) database, and outperformed than other state-of-the-art facial expression recognition methods.

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