Generalized elastic graph matching for face recognition

Elastic graph matching (EGM) is a well-known approach in face recognition area for the robust face recognition to a rotation in depth and facial expression change. We extended the conventional EGM to the generalized EGM (G-EGM), which is afford to handle even globally warped faces, by enhancing the robustness of node descriptors to a global warping, and introducing warping-compensated edges in graph matching cost function. The improved performance of the G-EGM was evaluated through the recognition simulation based on arbitrary posed faces.