2000 · 80 citations · 13 references
This paper describes building models which represent the appearance of an object (in particular, a face) as seen from two or more dierent viewpoints simultaneously. A small number of 2D linear statistical models are suÆcient to capture the shape and appearance of a face from a wide range of viewpoints. Given multiple images of the same face we can learn a coupled model describing the relationship between the frontal appearance and the prole of a face. This relationship can be used to predict new views of a face seen from one view. Such a coupled model can be used to constrain search algorithms which seek to locate a face in multiple views simultaneously, leading to more robust results than searching each view independently. 1
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Matthew Turk, Alex Pentland · Journal of Cognitive Neuroscience · 1991 · 13.7K citations · Full text
XM2VTSDB: The Extended M2VTS Database
Kieron Messer, Jiřı́ Matas, Josef Kittler et al. · 1999 · 1.2K citations · Full text
Interpreting face images using active appearance models
G. Edwards, Chris Taylor, T.F. Cootes · 2002 · 488 citations
View-based active appearance models
T.F. Cootes, Kevin Walker, Chris Taylor · 2002 · 250 citations
Geometric Modeling, Face Detection, Facial Recognition System +15