Beyond FACS: Data-driven Facial Expression Dictionaries, with Application to Predicting Autism.

ABSTRACT: The Facial Action Coding System (FACS) has been used by numerous studies to investigate the links between facial behavior and mental health. The laborious and costly process of FACS coding has motivated the development of machine learning frameworks for Action Unit (AU) detection. Despite intense efforts spanning three decades, the detection accuracy for many AUs is considered to be below the threshold needed for behavioral research. Also, many AUs are excluded altogether, making it impossible to fulfill the ultimate goal of FACS-the representation of any facial expression in its entirety. This paper considers an alternative approach. Instead of creating automated tools that mimic FACS experts, we propose to use a new coding system that mimics the key properties of FACS. Specifically, we c

SUBMITTER: Sariyanidi E 

PROVIDER: S-EPMC12369895 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature