Is your first impression reliable? Trustworthy analysis using facial traits in portraits

Abstract

As a basic human quality, trustworthiness plays an important role in social communications. In this paper, we proposed a novel concept to predict people’s trustworthiness at first sight using facial traits. Firstly, personalitytoward traits were designed from psychology, including permanent traits and transient traits. Then, a mixture of feature descriptors consisting of Histogram of Gradients (HOG), Local Binary Patterns (LBP) and geometrical descriptions were adopted to describe personality traits. Finally, we trained the personality traits by LibSVM to determine trustworthiness of a person using portrait. Experiments demonstrated the effectiveness of our method by improving the precision by 33.60%, recall by 20.33% and F1-measure by 25.63% when determining whether a person is trustworthy or not comparing to a baseline method. Feature contribution analysis was applied to deeply unveil the correspondence between features and personality. Demonstration showed visual patterns in portrait collages of trustworthy people that further proved effectiveness of our method.