Face recognition from multi-pose image sequence

A novel approach to face recognition based on multi-pose image sequence is presented in this paper. In this approach faces are represented by their pattern vectors (projections to eigenfaces) in eigenspace. Instead of recognizing a face from a single view, a sequence of images showing face movement (from left to the right profile) is used for recognition. Pattern vectors corresponding to multiple poses build a trajectory in eigenspace where each trajectory belongs to one face sequence (profile to profile). In the training phase, sequences of poses construct prototypes trajectories, and in recognition phase, an unknown face trajectory is taken into comparison with prototypes. New models of matching are presented and analyzed as well as influence of some parameters to recognition ratio.