In this paper, we propose a novel classification method, called local manifold matching (LMM), for face recognition. LMM has great representational capacity of available prototypes...
Real-time recognition may be limited by scarce memory and computing resources for performing classification. Although, prior research has addressed the problem of training classif...
Ashish Kapoor, Simon Baker, Sumit Basu, Eric Horvi...
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...
In this paper, we propose a new supervised linear feature extraction technique for multiclass classification problems that is specially suited to the nearest neighbor classifier (N...
This paper investigates the use of range images of faces for recognizing people. 3D scans of faces lead to range images that are linearly projected to low-dimensional subspaces fo...