We present a theory for constructing linear subspace approximations to face-recognition algorithms and empirically demonstrate that a surprisingly diverse set of face-recognition a...
This paper introduces a novel image decomposition approach for an ensemble of correlated images, using low-rank and sparsity constraints. Each image is decomposed as a combination...
In this paper, a discriminative manifold learning method for face recognition is proposed which achieved the discriminative embedding the high dimensional face data into a low dim...
This paper examines the the effectiveness of feature modelling to conduct 2D and 3D face recognition. In particular, PCA difference vectors are modelled using Gaussian Mixture Mod...
Chris McCool, Jamie Cook, Vinod Chandran, Sridha S...
We present an approach to recognizing faces with varying appearances which also considers the relative probability of occurrence for each appearance. We propose and demonstrate ex...
Nathan Mekuz, Christian Bauckhage, John K. Tsotsos