A new technique is discussed to estimate the pose (orientation) of unknown human faces from 2D gray-scale images and then transform the unknown face to a reference pose using a nonlinear feature extraction procedure. This feature extraction scheme is known as the maximum representation and discrimination feature (MRDF) method. The MRDF is shown to provide good features for discrimination between classes that is useful for pose estimation, and for object representation that is useful for pose transformation of an unknown face. Our approach is computationally efficient and has numerous potential applications, including post-invariant face recognition.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.