Robust Facial Landmark Localization for Automotive Applications

This paper introduces a novel system for facial landmark detection using a modified Active Appearance Model (AAM). Traditional AAMs operate directly on the pixel values of the image, leading to problems with inhomogeneously illuminated scenes. Instead of using the gray-level image to detect the facial landmark directly, the Modified Census Transformation (MCT) is performed on the region of interest (ROI) being analyzed, making the system invariant to illumination variations and nonlinear camera characteristics. To achieve efficient and robust fitting with regard to occluded or invisible parts of the face, parameter constraints, coarse to fine fitting and occlusion handling are introduced. The result shows that the new system yields good results even if some areas of the face are occluded or unrecognizable in the image.