Automatic estimation of the dynamics of facial expression using a three-level model of intensity

Facial expressions and their associated dynamics play an important role in human communication. The dynamics of facial expressions can be defined as the intensity and timing of their constituent components as they form. However, estimating the dynamics of facial expressions is a non trivial task. The majority of automatic approaches to characterising intensity use a two-level model (also known as onset-apex-offset). However the FACS specifies five intensity levels for each AU. In this paper we evaluate the efficacy of Local Linear Embedding as a means of estimating the intensity of facial expression. This is done using both the full five level FACS model, and a simplified three level model. We have found that using the FACS intensity scoring results in a considerable overlap between the estimated intensities. Using a three level model enables us to classify the intensities with significantly greater degree of accuracy.