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Proceedings Paper

3D face reconstruction from limited images based on differential evolution
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Paper Abstract

3D face modeling has been one of the greatest challenges for researchers in computer graphics for many years. Various methods have been used to model the shape and texture of faces under varying illumination and pose conditions from a single given image. In this paper, we propose a novel method for the 3D face synthesis and reconstruction by using a simple and efficient global optimizer. A 3D-2D matching algorithm which employs the integration of the 3D morphable model (3DMM) and the differential evolution (DE) algorithm is addressed. In 3DMM, the estimation process of fitting shape and texture information into 2D images is considered as the problem of searching for the global minimum in a high dimensional feature space, in which optimization is apt to have local convergence. Unlike the traditional scheme used in 3DMM, DE appears to be robust against stagnation in local minima and sensitiveness to initial values in face reconstruction. Benefitting from DE's successful performance, 3D face models can be created based on a single 2D image with respect to various illuminating and pose contexts. Preliminary results demonstrate that we are able to automatically create a virtual 3D face from a single 2D image with high performance. The validation process shows that there is only an insignificant difference between the input image and the 2D face image projected by the 3D model.

Paper Details

Date Published: 24 September 2011
PDF: 8 pages
Proc. SPIE 8135, Applications of Digital Image Processing XXXIV, 813518 (24 September 2011); doi: 10.1117/12.894253
Show Author Affiliations
Qun Wang, Old Dominion Univ. (United States)
Jiang Li, Old Dominion Univ. (United States)
Vijayan K. Asari, Univ. of Dayton (United States)
Mohammad A. Karim, Old Dominion Univ. (United States)

Published in SPIE Proceedings Vol. 8135:
Applications of Digital Image Processing XXXIV
Andrew G. Tescher, Editor(s)

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