Observers Pupillary Responses in Recognising Real and Posed Smiles: A Preliminary Study

TL;DR

This study investigates whether pupillary responses can distinguish between real and posed smiles, finding that responses to paired videos are most indicative, with implications for affective computing and human-computer interaction.

Contribution

It demonstrates that pupillary responses, especially to paired videos, can effectively differentiate real from posed smiles, a novel approach in emotion recognition research.

Findings

Pupillary responses differ significantly between real and posed smiles.

The most notable differences are observed in paired video stimuli.

The model can recognize smile authenticity from pupillary data.

Abstract

Pupillary responses (PR) change differently for different types of stimuli. This study aims to check whether observers PR can recognise real and posed smiles from a set of smile images and videos. We showed the smile images and smile videos stimuli to observers, and recorded their pupillary responses considering four different situations, namely paired videos, paired images, single videos, and single images. When the same smiler was viewed by observers in both real and posed smile forms, we refer them as paired; otherwise we use the term single. The primary analysis on pupil data revealed that the differences of pupillary response between real and posed smiles are more significant in case of paired videos compared to others. This result is found from timeline analysis, KS-test, and ANOVA test. Overall, our model can recognise real and posed smiles from observers pupillary responses instead of smilers responses. Our research will be applicable in affective computing and computer-human interaction for measuring emotional authenticity.