This paper describes a method to perform face pose estimation and high resolution facial feature extraction on the basis of stereoscopic color images. Unlike other approaches no light projection is required at running time. In our method face detection is based on color driven clustering of 3D points derived from stereo. A mesh model is registered with the post-processed face cluster using a variant of the Iterative Closest Point algorithm (ICP). Pose is derived from correspondence. Then, pose and model information is used for face normalization and facial feature localization. Results show, stereo and color are powerful cues for finding the face and its pose under a wide range of poses, illuminations and expressions (PIE). Head orientation may vary in out of plane rotations up to ? 45?.