Component-wise pose normalization for pose-invariant face recognition

The pose variation involved in facial images significantly degrades the performance of face recognition systems. In this paper, a component-wise pose normalization method for facilitating pose-invariant face recognition is proposed. The main idea is to normalize a non-frontal facial image to a virtual frontal image component by component. In this method, we first partition the whole non-frontal facial image into different facial components and then the virtual frontal view for each component is estimated separately. The final virtual frontal image is generated by integrating the virtual frontal components. The proposed method relies only on 2D images, therefore complex 3D modeling is not needed. The experimental results using the CMU-PIE database demonstrate the advantages of the proposed method.