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Received: 2006-02-10

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Journal of Zhejiang University SCIENCE A 2007 Vol.8 No.4 P.550~558

10.1631/jzus.2007.A0550


Sample based 3D face reconstruction from a single frontal image by adaptive locally linear embedding


Author(s):  ZHANG Jian, ZHUANG Yue-ting

Affiliation(s):  School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   zhangsdust@yahoo.com.cn, yzhuang@cs.zju.edu.cn

Key Words:  Face reconstruction, Manifold learning, RBF interpolation, Reconstruction error rate


ZHANG Jian, ZHUANG Yue-ting. Sample based 3D face reconstruction from a single frontal image by adaptive locally linear embedding[J]. Journal of Zhejiang University Science A, 2007, 8(4): 550~558.

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author="ZHANG Jian, ZHUANG Yue-ting",
journal="Journal of Zhejiang University Science A",
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pages="550~558",
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T1 - Sample based 3D face reconstruction from a single frontal image by adaptive locally linear embedding
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DOI - 10.1631/jzus.2007.A0550


Abstract: 
In this paper, we propose a highly automatic approach for 3D photorealistic face reconstruction from a single frontal image. The key point of our work is the implementation of adaptive manifold learning approach. Beforehand, an active appearance model (AAM) is trained for automatic feature extraction and adaptive locally linear embedding (ALLE) algorithm is utilized to reduce the dimensionality of the 3D database. Then, given an input frontal face image, the corresponding weights between 3D samples and the image are synthesized adaptively according to the AAM selected facial features. Finally, geometry reconstruction is achieved by linear weighted combination of adaptively selected samples. Radial basis function (RBF) is adopted to map facial texture from the frontal image to the reconstructed face geometry. The texture of invisible regions between the face and the ears is interpolated by sampling from the frontal image. This approach has several advantages: (1) Only a single frontal face image is needed for highly automatic face reconstruction; (2) Compared with former works, our reconstruction approach provides higher accuracy; (3) Constraint based RBF texture mapping provides natural appearance for reconstructed face.

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Reference

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