Optical flow techniques are becoming increasingly performant and robust when estimating motion in a scene, but their performance has yet to be proven in the area of facial expression recognition. In this work, a variety of optical flow approaches are evaluated across multiple facial expression datasets, so as to provide a consistent performance evaluation. The aim of this work is not to propose a new expression recognition technique, but to understand better the adequacy of existing state-of-the art optical flow for encoding facial motion in the context of facial expression recognition. Our evaluations highlight the fact that motion approximation methods used to overcome motion discontinuities have a significant impact when optical flows are used to characterize facial expressions.
@article{arxiv.1904.11592,
title = {Optical Flow Techniques for Facial Expression Analysis -- a Practical Evaluation Study},
author = {Benjamin Allaert and Isaac Ronald Ward and Ioan Marius Bilasco and Chaabane Djeraba and Mohammed Bennamoun},
journal= {arXiv preprint arXiv:1904.11592},
year = {2024}
}