Data collection for both training and testing a classifier is a tedious but essential step towards face detection and recognition. It is a piece of cake to collect more than hundre...
Most current 3D face recognition algorithms are designed based on the data collected in controlled situations, which leads to the un-guaranteed performance in practical systems. I...
In a sparse-representation-based face recognition scheme, the desired dictionary should have good representational power (i.e., being able to span the subspace of all faces) while...
Face recognition algorithms need to deal with variable
lighting conditions. Near infrared (NIR) image based face
recognition technology has been proposed to effectively
overcome...
In this paper, we develop a geometric framework for linear or nonlinear discriminant subspace learning and classification. In our framework, the structures of classes are conceptu...