Occlusion analysis for face frontalization

Frontalization is the process of generating frontal faces from the posed ones appearing in unconstrained environments. Occluders occurring over the face region can make the frontalization approaches generate faulty results. In this study, we propose an approach, to address this problem by reducing negative effects of occluders on the frontalization operation. The proposed approach has the capability of choosing the most suitable frontalization procedure, to generate a more visually appealing output. After the posed face image is hard-frontalized, the possible occlusion occurrences over the face are analyzed using two different techniques; region and pixel based analysis. Finally, according to occlusion analysis output, the best approach for frontalization process is chosen to be applied. The experiments performed on Caltech Occluded Faces Database (COFW) show that the proposed algorithm produces satisfactory results in terms of accuracy and visual appearance.