Recognition of facial images with subspace projection and dissimilarity representation

In this work, we present a framework for face recognition, combining face detection algorithm, dimensionality reduction method and a dissimilarity-based classifier. The face detection algorithm is intended to detect and extract faces in complex scenes, prior to face recognition. The Spectral Regression method, in sparse setting, is used for dimensionality reduction. The classification problem is solved by the Proximity Index ”Shape Coefficient” with SVM decision rules and Prototype Selection based classification. The results with real world experiments encourage us to propose this framework as good alternative to other face recognition methods.