MYFED: a dataset of affective face videos for investigation of emotional facial dynamics as a soft biometric for person identification

Abstract

Psychological studies have demonstrated that the facial dynamics play a significant role in recognizing an individual's identity. This study introduces a novel database (MYFED) and approach for person identification based on facial dynamics, to extract the identity-related information associated with the facial expressions of the six basic emotions (happiness, sadness, surprise, anger, disgust, and fear). Our contribution includes the collection of the MYFED database, featuring facial videos capturing both spontaneous and deliberate expressions of the six basic emotions. The database is uniquely tailored for person identification using facial dynamics of emotional expressions, ensuring an average of ten repetitions for each emotional expression per subject-a characteristic often absent in existing facial expression databases. Additionally, we present a novel person identification method leveraging dynamic features extracted from videos depicting the six basic emotions. Experimental results confirm that dynamic features of all emotional expressions contain identity-related information. Notably, surprise, happiness, and sadness expressions exhibit the highest levels of identity-related data in descending order. To our knowledge, this is the first research that comprehensively analyzes facial expressions of all six basic emotions for person identification. For further research and exploration, the MYFED database is made accessible to researchers via the MYFED database website.