Supervised classification of facial expressions

Over the last decade, the statistical analysis of facial expressions has become an active research topic that finds potential applications in many areas. As the expression plays remarkable social interaction, the development of a system that accomplishes the task of automatic classification is challenging. In this work, we thus consider the problem of classifying facial expressions through shape variables represented by log-transformed Euclidean distances computed among a set of anatomical landmarks