Automatic and Robust 2D/3D Human Face Landmarking

Face landmarking is a critical step for registration and normalization of both two and three-dimensional (2D and 3D) face images. Illumination and pose variations create challenging conditions for the accuracy and robustness of facial landmarking. These challenges can be managed by utilizing graph-based methods that incorporate some anthropometrical information and by using 2D jointly with 3D data. In this work, we propose two graph techniques to ruggedize facial landmarking and evaluate the contributions of various parameters to the accuracy. Proposed algorithms are cross-tested in different datasets to evaluate the performances.