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http://hdl.handle.net/20.500.12358/25077
TitleReconstructing 3D face shapes from single 2D images using an adaptive deformation model
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Abstract

The Representational Power (RP) of an example-based model is its capability to depict a new 3D face for a given 2D face image. In this contribution, a novel approach is proposed to increase the RP of the 3D reconstruction PCA-based model by deforming a set of examples in the training dataset. By adding these deformed samples together with the original training samples we gain more RP. A 3D PCA-based model is adapted for each new input face image by deforming 3D faces in the training data set. This adapted model is used to reconstruct the 3D face shape for the given input 2D near frontal face image. Our experimental results justify that the proposed adaptive model considerably improves the RP of the conventional PCA-based model.

Authors
Maghari, Ashraf Y. A.
Venkat, Ibrahim
Liao, Iman YI
Belaton, Bahari
TypeJournal Article
Date2013
Subjects
3d face reconstruction
tps
representational power
statistical facial modeling
pca
Published inInternational Visual Informatics Conference
PublisherSpringer, Cham
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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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