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In this paper, we presented an approach for automatic face verification from range data. The method consists of profile and surface matching. The profile is extracted on the basis of symmetry of human face, and a global profile matching method based on k-th Hausdorff distance is used to align and compare profiles, without detection of fiducial points that is often unreliable. For each individual, a statistical model of facial surface is built to represent the distinct discriminative capability of the different parts in the facial surface. Then the model is incorporated into a weighted distance function to measure similarity of surfaces. Finally two experts are combined to give a decision. The comparable experimental results are obtained on a database with 180 pieces of range data of 30 individuals.