An Effective Approach to Pose Invariant 3D Face Recognition
One critical challenge encountered by existing face recognition techniques lies in the difficulties of handling varying poses. In this paper, we propose a novel pose invariant 3D face recognition scheme to improve regular face recognition from two aspects. Firstly, we propose an effective geometry b...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2011
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/2357 https://ink.library.smu.edu.sg/context/sis_research/article/3357/viewcontent/An_Effective_Approach_to_Pose_Invariant_3D_Face_Recognition.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | One critical challenge encountered by existing face recognition techniques lies in the difficulties of handling varying poses. In this paper, we propose a novel pose invariant 3D face recognition scheme to improve regular face recognition from two aspects. Firstly, we propose an effective geometry based alignment approach, which transforms a 3D face mesh model to a well-aligned 2D image. Secondly, we propose to represent the facial images by a Locality Preserving Sparse Coding (LPSC) algorithm, which is more effective than the regular sparse coding algorithm for face representation. We conducted a set of extensive experiments on both 2D and 3D face recognition, in which the encouraging results showed that the proposed scheme is more effective than the regular face recognition solutions |
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