Facial landmark localization is a crucial step in many facial image analysis applications. In this paper, we propose a
combined ASEF (the average of synthetic exact filter) and pictorial structure method for facial landmark detection. First,
the local-maximums of the ASEF response image for each landmark are extracted as candidates. Then, the ASEF
response of candidates for each landmark and their relative positions are evaluated by the pictorial structure model.
Finally, the combination of candidates with highest score is selected as the final detection result. We show that by
introducing the position constraint to ASEF, the detection accuracy can be highly improved. The experimental results on
the BioID dataset verify the efficiency and accuracy of proposed method.