Initial Investigation into Using Two-Level Regional Voting Approach for Face Verification

Face verification is defined as a person whose identity is claimed a priori will be compared with the person´s individual template in database, and then the system checks whether the similarity between pattern and template is sufficient to provide access. In this paper we introduce a new procedure of face verification with an embedding Electoral College framework, which has been applied successfully in face identification. The approaches are evaluated by experiments on benchmark face databases applying the Electoral College framework embedded with standard baseline PCA (Principle Component Analysis) algorithm and newly developed algorithm S-LDA (Spatially Smooth Version of Linear Discriminant Analysis). The results demonstrate that the proposed face verification systems improve the performance of these holistic algorithms.