Pose-invariant recognition of faces at unknown aspect views

A new technique is discussed to recognize human faces under varying aspect views (pose). We first estimate the pose of an unknown human face from a 2D gray-scale image and then transform the unknown face to a reference pose using a feature extraction procedure. A different set of features for discriminating between different individuals are then extracted from these reconstructed faces for recognition. The feature extraction scheme used is known as the maximum representation and discrimination feature method. The advantage of our procedure is that it inherently removes distortions due to pose variations, and therefore requires only single training and/or test face images, which could be at different aspect views. For transformation, it does not require the face to be in the database during training. For recognition, only one aspect view at any pose is necessary