Abstract
Face recognition in unconstrained environments is often influenced by pose variations. And the problem is basically the identification that uses partial data. In this paper, a method fusing structure and texture information is proposed to solve the problem. In the register phase, the approximate 180 degree information of face is acquired, and the data used to identify individual is obtained from a random single view. Pure face is extracted from 3D data first, then convert the original data to the form of spherical depth map (SDM) and spherical texture map (STM), which are invariant to out-plane rotation, subsequently facilitating the successive alignment-free identification that is robust to pose variations. We make identification through sparse representation for its well performance with the two maps. Experiments show that our proposed method gets a high recognition rate with pose and expression variations.
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Liu, S., Mu, Z., Huang, H. (2015). 3D Face Recognition Fusing Spherical Depth Map and Spherical Texture Map. In: Yang, J., Yang, J., Sun, Z., Shan, S., Zheng, W., Feng, J. (eds) Biometric Recognition. CCBR 2015. Lecture Notes in Computer Science(), vol 9428. Springer, Cham. https://doi.org/10.1007/978-3-319-25417-3_19
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DOI: https://doi.org/10.1007/978-3-319-25417-3_19
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