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Seventh IEEE International Conference on Automatic Face and Gesture Recognition (FG'06)
Minimum Variance Estimation of 3D Face Shape from Multi-view
University of Southampton,UK
April 10-April 12
ISBN: 0-7695-2503-2
Zhenqiu Zhang, University of Illinois
Yuxiao Hu, University of Illinois
Tianli Yu, University of Illinois
Thomas Huang, University of Illinois
A minimum variance estimation framework for 3D face reconstruction from multiple views and a new 3D surface reconstruction algorithm based on deformable subdivision mesh is proposed in this paper. First, an efficient 2D-to-3D integrated face reconstruction approach is introduced to reconstruct a personalized 3D face model from a single frontal face image with minimum variance estimation; Then, a new deformable mesh based surface reconstruction algorithm is applied to the images from different views to get more observation of the 3D face, especially the depth information, which could not be obtained from a single image directly; Based on the result of the 3D surface reconstruction, we use the minimum variance estimation again to refine the estimation of the 3D face. We combine the texture from different views, and the result looks photorealistic.
Citation:
Zhenqiu Zhang, Yuxiao Hu, Tianli Yu, Thomas Huang, "Minimum Variance Estimation of 3D Face Shape from Multi-view," fg, pp.547-552, Seventh IEEE International Conference on Automatic Face and Gesture Recognition (FG'06), 2006
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