Do˘ gal ve Yapma G ¨ ul ¨ uslerin Siniflandirilmasi Classification of Spontaneous and Posed Smiles

Automatic detection of affective states from facial images and videos is a very important application in social signal process- ing. In this study we focus on the expression of happiness, and propose a physiologically inspired approach for detecting whether a smile is spontaneously produced or not. We use distance-based and angular features that characterize move- ments of facial regions, and train local classifiers for smile clas- sification. Our experiments with different classifiers on two dif- ferent datasets show that the eyelid region can be very useful in assessing spontaneous versus posed smiles.