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- W2279969272 abstract "Active Appearance Models (AAM) are able to align known faces in an efficient manner when face pose and illuminationare controlled. The AAM exploit a set of face examples in order to extract a statistical model. There is no difficulty toalign a face with the same type (same morphology, illumination and pose) which constitute the example data set.Unfortunately, the AAM are less outstanding from the moment when the illumination, pose and face type changes.AAM robustness is link to the variability introduced in the learning base. The more the AAM will contain variability, themore it will be able to adapt itself to variable faces with the following drawback : the data represented in the reducedparameters space will then form different classes letting appear holes, regions without any data (see Fig. 1). It istherefore very difficult to make the AAM converge in this scattered space.We propose in this paper a robust Active Appearance Models allowing a real-time implementation. To increase the AAMrobustness to illumination changes, we propose Oriented Map AAM (OM-AAM). Adapted AAM will be presented after toincrease the AAM robustness to any other types of variability (in identity, pose, expression etc.)..." @default.
- W2279969272 created "2016-06-24" @default.
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- W2279969272 date "2008-02-05" @default.
- W2279969272 modified "2023-10-09" @default.
- W2279969272 title "Modèles actifs d'apparences adaptés" @default.
- W2279969272 hasPublicationYear "2008" @default.
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