Effect of Facial Expressions on Feature-Based Landmark Localization in Static Grey Scale Images

The present aim was to examine the effect of facial expressions on the feature-based landmark localization in static grey scale images. In the method, local oriented edges were extracted and edge maps of the image were constructed at two levels of resolution. Regions of connected edges represented landmark candidates and were further verified by matching against the edge orientation model. The method was tested on a large database of expressive faces coded in terms of action units. Action units described single and conjoint facial muscle activations in upper and lower face. As results demonstrated, eye regions were located with high rates in both neutral and expressive datasets. Nose and mouth localization was more attenuated by variations in facial expressions. The present results specified some of the critical facial behaviours that should be taken into consideration while improving automatic landmark detectors which rely on the low-level edge and intensity information.