  The analysis of expression and facial Action Units (AUs) detection are very
important tasks in fields of computer vision and Human Computer Interaction
(HCI) due to the wide range of applications in human life. Many works has been
done during the past few years which has their own advantages and
disadvantages. In this work we present a new model based on Gaussian
Conditional Random Field. We solve our objective problem using ADMM and we show
how well the proposed model works. We train and test our work on two facial
expression datasets, CK+ and RU-FACS. Experimental evaluation shows that our
proposed approach outperform state of the art expression recognition.
