In this paper, we present results on experiments employing Active Appearance Model (AAM) derived facial representations, for the task of facial action recognition. Experimental results demonstrate the benefit of AAM-derived representations on a spontaneous AU database containing “real-world” variation. Additionally, we explore a number of normalization methods for these representations which increase facial action recognition performance.