Abstract
The smile is a frequently expressed facial expression that typically conveys a positive emotional state and friendly intent. However, human beings have also learned how to fake smiles, typically by controlling the mouth to provide a genuine-looking expression. This is often accompanied by inaccuracies that can allow others to determine that the smile is false. Mouth movement is one of the most striking features of the smile, yet our understanding of its dynamic elements is still limited. The present study analyzes the dynamic features of lip corners, and considers how they differ between genuine and posed smiles. Employing computer vision techniques, we investigated elements such as the duration, intensity, speed, symmetry of the lip corners, and certain irregularities in genuine and posed smiles obtained from the UvA-NEMO Smile Database. After utilizing the facial analysis tool OpenFace, we further propose a new approach to segmenting the onset, apex, and offset phases of smiles, as well as a means of measuring irregularities and symmetry in facial expressions. We extracted these features according to 2D and 3D coordinates, and conducted an analysis. The results reveal that genuine smiles have higher values for onset, offset, apex, and total durations, as well as offset displacement, and a variable we termed Irregularity-b (the SD of the apex phase) than do posed smiles. Conversely, values tended to be lower for onset and offset Speeds, and Irregularity-a (the rate of peaks), Symmetry-a (the correlation between left and right facial movements), and Symmetry-d (differences in onset frame numbers between the left and right faces). The findings from the present study have been compared to those of previous research, and certain speculations are made.