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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Mixed 2D-3D Information for Face Recognition
verfasst von : Hengliang Tang, Yanfeng Sun, Baocai Yin, Yun Ge
Erschienen in: Transactions on Edutainment V
Verlag: Springer Berlin Heidelberg
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Face recognition with assistance of 3D models has been a successful approach recently. In this paper, we develop a face recognition system fusing 2D and 3D face information. First, the HarrLBP representation is proposed to represent the 2D faces. Then, the 3D morphable model (3DMM) is employed to estimate the 3D shape for the given 2D face, and five kinds of 3D facial geometrical features are extracted from the virtual 3D facial meshes to assist the face recognition. Finally, we fuse the 2D HarrLBP and the five 3D features under a linear self-adaptive weight scheme to promote the final recognition efficiency. The experimental results on ORL and JAFFE2 face database show the good performance of the proposed fusion method, and demonstrate that our method is robust to the facial expressions and poses to a certain extent.