Landmark Based Facial Component Reconstruction for Recognition across Pose

Different from previous 3D face modeling approaches that consider the whole facial area, the proposed method reconstructs 3D facial components for handling cross-pose recognition. It has two phases, component reconstruction and component-based recognition. In the reconstruction phase, we first extract four component regions, namely two eyes, nose and mouth, from each gallery face using the pose-invariant landmarks obtained by a modified version of a landmark detection algorithm. A 3D model of each component region is reconstructed using a constrained minimization scheme with a gender and ethnicity oriented 3D model as the reference. In the recognition phase, the pose of a given probe is determined by a set of landmarks which guides the rotation of the reconstructed components so that the reconstructed can be aligned to the probe components. The match is determined by the components instead of the whole faces so that different components can be considered at different poses. Experiments on the PIE and Multi-PIE databases show that the proposed component-based approach does not just outperform its holistic counterpart, but is also competitive to many contemporary methods.