3-D Shape Matching for Face Analysis and Recognition
2015
The aims of this paper are to introduce a 3-D shape matching scheme for automatic face recognition and to
demonstrate its invariance to pose and facial expressions. The core of this scheme lies on the combination of
non-rigid deformation registration and statistical shape modelling. While the former matches 3-D faces
regardless of facial expression variations, the latter provides a low-dimensional feature vector that describes
the deformation after the shape matching process, thereby enabling robust identification of 3-D faces. In
order to assist establishment of accurate dense point correspondences, an isometric embedding shape
representation is introduced, which is able to transform 3-D faces to a canonical form that retains the
intrinsic geometric structure and achieve shape alignment of 3-D faces independent from individualâs facial
expression. The feasibility and effectiveness of the proposed method was investigated using standard
publicly available Gavab and BU-3DFE databases, which contain faces expressions and pose variations.
The performance of the system was compared with the existing benchmark approaches and it demonstrates
that the proposed scheme provides a competitive solution for the face recognition task with real-world
practicality.
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