3D Facial Feature Localization for Registration

Accurate automatical localization of fiducial points in face images is an important step in registration. Although statistical methods of landmark localization reach high accuracies with 2D face images, their performances rapidly deteriorate under illumination changes. 3D information can assist this process by either removing the illumination effects from the 2D image, or by supplying robust features based on depth or curvature. We inspect both approaches for this problem. Our results indicate that using 3D features is more promising than illumination correction with the help of 3D. We complement our statistical feature detection scheme with a structural correction scheme and report our results on the FRGC face dataset.