3D facial expression synthesis from a single image using a model set
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
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In this paper, we propose a new algorithm for shape initialization and 3D pose alignment in Active Shape Model (ASM). Instead of initializing with average shape in previous works, we build a scatter data interpolation model from key points to obtain the initial shape, which ensures shape initialized around face organs. These key points are chosen from organs of face shape and located with a strong classifier firstly. Then they are utilized to build a Radial Basis Function (RBF) model to deform the average shape as initial shape. Besides, to cope with variety face poses, we define a 3D general shape to align face shapes in 3D instead of 2D alignment in Classic ASM. With the accurate 3D rotation angles iteratively calculated by Levenberg-Marquardt (LM) algorithm, shapes can be aligned to standard shape more reliably. Experiments and comparisons on FERET show that both shape initialization and 3D pose alignment of our algorithm greatly improve the location accuracy.