Techniques for the 3-D analysis of facial shape changes resulting from growth or surgical treatment have recently been proposed. These approaches rely on manual intervention for placing anatomical landmarks on 3-D facial models which is time consuming and error prone. In this paper, an automated approach to landmark extraction is described which uses a stereo-assisted active shape model. A landmark-based statistical analysis of facial shape change is then carried out using procrustes registration, principal component analysis and thin plate spline warping. The proposed method is validated both statistically and visually by characterizing shape changes induced by mandibular repositioning in a cross-sample of 20 orthodontic patients. It is shown that the method is capable of distinguishing between changes in facial morphology due to mandibular repositioning and changes due to other factors such as growth and normal variation within the patient sample.
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