In order for a subspace projection based method to be robust to local distortion and partial occlusion, the basis images generated by the method should exhibit a part-based local r...
In this paper, we propose a novel method, called local nonnegative matrix factorization (LNMF), for learning spatially localized, parts-based subspace representation of visual pat...
Stan Z. Li, XinWen Hou, HongJiang Zhang, QianSheng...
Non-negative matrix factorization (NMF) is an excellent tool for unsupervised parts-based learning, but proves to be ineffective when parts of a whole follow a specific pattern. ...
We present a robust elastic and partial matching metric
for face recognition. To handle challenges such as pose, facial
expression and partial occlusion, we enable both elastic
...
In this paper, we propose a novel occlusion invariant face recognition algorithm based on Selective Local Nonnegative Matrix Factorization (S-LNMF) technique. The proposed algorith...
Hyun Jun Oh, Kyoung Mu Lee, Sang Uk Lee, Chung-Hyu...