DCT based facial feature extraction

In this paper we introduced an automatic landmarking method for near-frontal face images based on DCT coefficients. The face information is provided as 480x640 gray-level images with 3D scene depth data. Range data is used to eliminate the background data from the face. The proposed facial landmarking algorithm uses a coarse-to-fine searching algorithm. In coarse level the images are downsampled to 80x60 pixels resolution. Both in coarse and fine levels SVM classifiers are trained using the DCT coefficients extracted from the manually landmarked training data. Coarse level candidate facial points are searched within the whole face image. Once the candidate locations are established, we revert back to the higher resolution image and refine the accuracy by using search windows around the coarse landmark locations.