Wyniki wyszukiwania:

Face recognition algorithm perform very unreliably when the pose of the probe face is different from the stored face typical feature vectors vary more with pose than with identity. We propose a generative model that creates a one-to-many mapping from an idealized "identity" space to the observed data space. In this identity space, the representation for each individual does not vary with pose. The measured feature vector is generated by a pose contingent linear transformation of the identity vector in the presence of noise. Existing methods for performing face recognition in the presence of...