A Novel Framework for Face Recognition in Real-Time Environments
In this paper, the authors propose a novel frame work for face recognition in real-time environments using the Principal Component Analysis (PCA)-based face recognition methodology. The proposed frame work is developed by three schemes namely, nonlinearity clustering, Eigen vector mapping and relationship learning. In the beginning, a clustering algorithm is proposed as a preprocessing step. After clustering, the Very Low Resolution (VLR), High Resolution (HR), Illuminated Image (IL) pairs in every cluster is approximate nonlinear, i.e., the relationship will be approximately represented by a matrix.