Conditions for Viewpoint Dependent Face Recognition

摘要

Poggio and Vetter showed that learning one view of a bilaterally symmetric objectcould be sufficient for its recognition, if this view allows the computation of a symmetric, virtual view. Faces are roughly bilaterally symmetric objects. Learning a side-view-which always has a symmetric view-should allow for better generalization performances than learning the frontal view. Two psychophysical experiments tested these predictions. Stimuli were views of shaded 3D models of laser-scanned faces. The first experiment tested whether a particular view of a face was canonical. The second experiment tested which single views of a face give rise to best generalization performances. (AN).