Motion Dynamic Analysis of the Basic Facial Expressions

Abstract

In interaction systems, communication between user and the computer may be performed using a graphical display of human representation called avatar. This paper is focussed on the problem of facial motion analysis for human-like animation. Using similarities in motion data four criteria for characteristic points grouping (facial regions, movement directions, angles and distances) have been proposed. In order to estimate the number of clusters for selected facial expressions a dedicated algorithm has been applied. Based on the results of subjective assessment the most satisfying configuration of criteria, in terms of number of clusters and accuracy of emotions recognition, was a group of distance, region and angle between facial markers. In the result, the obtained groups may be used to simplify the number of control parameters necessary to synthesise facial expressions in virtual human systems. The final structure of the characteristic points can diminish overall computational resources usage by decreasing the number of points that need to be recalculated between animation phases. This is due to the fact, that the movement similarities were exploited to make the groups with the same properties be controlled by dominant markers.