The field of computer vision endeavours to develop automatic approaches to the interpretation of images from the real world. Over the past number of decades researchers within this field have created systems specifically for the automatic analysis of facial expression. The most successful of these approaches draw on the tools from behavioural science. In this chapter we examine facial expression analysis from both a behavioural science and a computer vision perspective. First we will provide details of the principal approach used in behavioural science to analyse facial expressions.
This will include an overview of the evolution of facial expression analysis, where we introduce the field of facial expression analysis with Darwin’s initial findings (Darwin, 1872). We then go on to show how his findings were confirmed nearly 100 years later by Ekman et al. (Ekman et al., 1969).
Following on from this we provide details of recent works investigating the appearance and
dynamics of facial expressions. Given these foundations from behavioural science, we appraise facial expression analysis from a computer vision perspective. Here researchers attempt to create automated computational models for facial expression classification and synthesis. This chapter is divided into three sections, each of which deals with a different, but related problem within the field of facial expression analysis:
