Patch-based representation of visual speech
VisHCI '06 Proceedings of the HCSNet workshop on Use of vision in human-computer interaction - Volume 56
A Viewpoint Invariant, Sparsely Registered, Patch Based, Face Verifier
International Journal of Computer Vision
Image and Vision Computing
Probabilistic learning for fully automatic face recognition across pose
Image and Vision Computing
Towards pose-invariant 2D face classification for surveillance
AMFG'07 Proceedings of the 3rd international conference on Analysis and modeling of faces and gestures
Bayesian prior models for vehicle make and model recognition
Proceedings of the 7th International Conference on Frontiers of Information Technology
Cross-pose face recognition based on partial least squares
Pattern Recognition Letters
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Most pose robust face verification algorithms, which employ 2D appearance, rely heavily on statistics gathered from offline databases containing ample facial appearance variation across many views. Due to the high dimensionality of the face images being employed, the validity of the assumptions employed in obtaining these statistics are essential for good performance. In this paper we assess three common approaches in 2D appearance pose mismatched face recognition literature. In our experiments we demonstrate where these approaches work and fail. As a result of this analysis, we additionally propose a new algorithm that attempts to learn the statistical dependency between gallery patches (i.e. local regions of pixels) and the whole appearance of the probe image. We demonstrate improved performance over a number of leading 2D appearance face recognition algorithms.