Conditions for Viewpoint Dependent Face Recognition.
Abstract
Poggio and Vetter showed that learning one view of a bilaterally symmetric object could 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)
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 1993
- Accession Number
- ADA290098
Entities
People
- Heinrich H. Buelthoff
- Philippe G Schyns
Organizations
- Massachusetts Institute of Technology