In this paper, we propose a fully automatic, effective and efficient
\nframework for 3D face reconstruction based on a single face image in
\narbitrary view. First, a multi-view face alignment algorithm localizes the
\nface feature points, and then EM algorithm is applied to derive the optimal
\n3D shape and position parameters. Moreover, the unit quaternion
\nbased pose representation is proposed for efficient 3D pose parameter optimization.
\nCompared with other related works, this framework has the
\nfollowing advantages: 1) it is fully automatic, and only one single face
\nimage in arbitrary view is required; 2) EM algorithm and unit quaternion
\nbased pose representation are integrated for efficient shape and position
\nparameters estimation; 3) the correspondence between 2D contour points
\nand 3D model vertexes are dynamically determined by normal direction
\nconstraints, which facilitates the 3D reconstruction from arbitrary view
\nimage; 4) a weighted optimization strategy is applied for more robust
\nparameter estimation. The experimental results show the effectiveness
\nof our framework for 3D face reconstruction.<\/p>\n","protected":false},"excerpt":{"rendered":"
In this paper, we propose a fully automatic, effective and efficient framework for 3D face reconstruction based on a single face image in arbitrary view. First, a multi-view face alignment algorithm localizes the face feature points, and then EM algorithm is applied to derive the optimal 3D shape and position parameters. 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