Manifold-based constraints for operations in face space
作者：
Highlights：
• We decompose statistical face models into identity and distinctiveness subspaces.
• The identity subspace forms a hyperspherical manifold that we validate empirically.
• The manifold provides non-linear alternatives to warping and averaging.
• We use the manifold to constrain optimisation-based model fitting.
• This outperforms two existing algorithms on over- and under-constrained problems.
摘要
Highlights•We decompose statistical face models into identity and distinctiveness subspaces.•The identity subspace forms a hyperspherical manifold that we validate empirically.•The manifold provides non-linear alternatives to warping and averaging.•We use the manifold to constrain optimisation-based model fitting.•This outperforms two existing algorithms on over- and under-constrained problems.
论文关键词：Optimisation on manifolds,Face space,3D morphable models,Constrained optimisation,Statistical modelling
论文评审过程：Received 18 March 2015, Revised 25 August 2015, Accepted 3 October 2015, Available online 22 October 2015, Version of Record 24 December 2015.
论文官网地址：https://doi.org/10.1016/j.patcog.2015.10.003
