Facial Action Recognition for Facial Expression Analysis From Static Face Images

TLDR

Automatic recognition of facial gestures is an increasingly important area in machine vision. The authors present an automated system for recognizing facial gestures in static frontal or profile color face images. The system localizes facial features with a multidetector, samples profile and component contours, extracts 10 profile and 19 component fiducial points, and uses rule‑based reasoning to recognize 32 facial muscle actions with certainty factors. The system achieves an 86 % recognition rate.

Abstract

Automatic recognition of facial gestures (i.e., facial muscle activity) is rapidly becoming an area of intense interest in the research field of machine vision. In this paper, we present an automated system that we developed to recognize facial gestures in static, frontal- and/or profile-view color face images. A multidetector approach to facial feature localization is utilized to spatially sample the profile contour and the contours of the facial components such as the eyes and the mouth. From the extracted contours of the facial features, we extract ten profile-contour fiducial points and 19 fiducial points of the contours of the facial components. Based on these, 32 individual facial muscle actions (AUs) occurring alone or in combination are recognized using rule-based reasoning. With each scored AU, the utilized algorithm associates a factor denoting the certainty with which the pertinent AU has been scored. A recognition rate of 86% is achieved.