Finding the Importance of Facial Features in Social Trait Perception

We are constantly making very fast attributions from faces, such as whether a person is trustworthy or threatening, that influence our behavior towards people. In this work, we present a method to automatically tell the importance of facial features on social trait perception. We employ an unsupervised clustering method to group the facial features by similarity and then create a model which explains the contribution of each facial feature to each social trait by means of a Genetic Algorithm. Our model deals with the difficulties associated to quantifying social impression using judgments from human observers (low inter- and intra-observer agreement) and obtains significant correlations greater than 0.7 for all social impressions, which justifies the method developed. Finally, the weights of the eyebrows, eyes, nose, mouth, jawline and facial feature distances are shown and discussed. This work poses a step forward in social trait impression understanding, as to the date, there is no other work quantifying the effects of facial features on social trait perception.