3D face landmark auto detection

This paper presents our methodology for Landmark Point detection to improve 3D face recognition in a presence of variant facial expression. The objective was to develop an automatic process for distinguishing and segmenting to be embedded in a 3D face recognition system using only 3D Point Distribution Model (PDM) as input. The approach used hydride method to extract this features from the surface curvature information. Landmark Localization is done on the segmented face via finding the change that decreases the deviation of the model from the mean profile. Face registering is achieved using previous anthropometric information and the localized landmarks. The results confirm that the method used is accurate and robust for the proposed application.