Multi-manifold learning using locally linear embedding(LLE) nonlinear dimensionality reduction
Jiaxin Wang · Journal of Tsinghua University(Science and Technology) · 2008
A variant of the locally linear embedding (LLE) technique is used to learn multiple low-dimensional facial expression manifolds formed by multiple subjects with multiple expressions the algorithm first separates the multivariate expression data distributed on several disjoint manifolds into different groups and then analyzes the intrinsic dimensionality and the low-dimensional manifold representation for each group of data. The simultaneous data grouping and the intrinsic dimension detection are both automatic, with reasonable computational loads. Recognition tests using the on Cohn-Kanade facial expression database show that the algorithm is superior to the original LLE in terms of the multi-manifold subspace learning, increasing the expression recognition rate from 20% to 40%.