A method to Suppress Facial Expression in Posed and Spontaneous Videos

TL;DR

This paper introduces an optical strain suppression technique that neutralizes facial expressions in videos without needing expression-specific training, aiding face recognition tasks.

Contribution

The method effectively suppresses various facial expressions in videos using optical strain maps without requiring prior training for specific expressions.

Findings

Successfully suppresses happiness, sadness, and anger expressions

Works on publicly available datasets BU-4DFE and AM-FED

Enhances face recognition by neutralizing expressions

Abstract

We address the problem of suppressing facial expressions in videos because expressions can hinder the retrieval of important information in applications such as face recognition. To achieve this, we present an optical strain suppression method that removes any facial expression without requiring training for a specific expression. For each frame in a video, an optical strain map that provides the strain magnitude value at each pixel is generated; this strain map is then utilized to neutralize the expression by replacing pixels of high strain values with pixels from a reference face frame. Experimental results of testing the method on various expressions namely happiness, sadness, and anger for two publicly available data sets (i.e., BU-4DFE and AM-FED) show the ability of our method in suppressing facial expressions.