Abstract

Face recognition based on 2D images is a difficult problem, because the illumination, pose and expression changes in the images create great statistical differences and the identity of the face itself becomes shadowed by these factors. 3D face recognition has the potential to overcome feature localization, pose and illumination problems, and it can be used in conjunction with 2D systems. We review the relevant work on 3D face recognition here, and discuss merits and demerits of different representations and recognition algorithms. This survey focuses on 3D face data acquisition and 3D face recognition using histogram features. Future works involved in developing more accurate 3D face recognition are also discussed. These include the need for improved 3D face data acquisition, 3D face recognition algorithms and 3D face experimental methodology.

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