Comparison of methods for smile deceit detection by training AU6 and AU12 simultaneously

Smiles play an important role in face to face interaction which is a human-specific direct and naturally preeminent way of communication. People smile out of various reasons. Some smiles are spontaneous while some others are just posed. It is hard for human to catch such subtle differences between the two different smiles. In this paper, different algorithm combinations are tried to realize the deceit detection of smiles by computer, that is to say, to recognize true (spontaneous) and fake (posed) smiles. The detection is based on AUs (facial action units). Moreover, AU6 and AU12 are dealt with together in each example, which is different from AU recognition. Images in our database are all frontal facial images with smiles of different types and levels, which are from subjects of different countries and ages with different colors. Experiments are implemented to find out which algorithm combination is the best one. Results show that the best accuracy of the tried combinations in detecting true and fake smiles is close to 86%, while human true-fake-smile recognition ability is much lower. Our work could be used as a tool for the analysis of smiles in psychological area and other regions.