Multidimensional Morphable Models: A Framework for Representing and Matching Object Classes
International Journal of Computer Vision
An Illumination-Insensitive Face Matching Algorithm
PCM '02 Proceedings of the Third IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Non-parametric and light-field deformable models
Computer Vision and Image Understanding
Classification of face images using local iterated function systems
Machine Vision and Applications
Efficient statistical face recognition across pose using local binary patterns and Gabor wavelets
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Domain adaptive dictionary learning
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
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If we are provided a face database with only one example view per person, is it possible to recognize new views of them under a variety of different poses, especially views rotated in depth from the original example view? We investigate using prior knowledge about faces plus each single example view to generate {\it virtual views} of each person, or views of the face as seen from different poses. Prior knowledge of faces is represented in an example-based way, using 2D views of a prototype face seen rotating in depth. The synthesized virtual views are evaluated as example views in a view-based approach to pose-invariant face recognition. They are shown to improve the recognition rate over the scenario where only the single real view is used.