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3D morphable face models revisited
2009
2009 IEEE Conference on Computer Vision and Pattern Recognition
In this paper we revisit the process of constructing a high resolution 3D morphable model of face shape variation. We demonstrate how the statistical tools of thin-plate splines and Procrustes analysis can be used to construct a morphable model that is both more efficient and generalises to novel face surfaces more accurately than previous models. We also reformulate the probabilistic prior that the model provides on the distribution of parameter vector lengths. This distribution is determined
doi:10.1109/cvpr.2009.5206522
dblp:conf/cvpr/PatelS09
fatcat:we72zwao5bbr3aesgreezh5sh4