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3D Active Appearance
Model for Aligning Faces in 2D Images
Chun-Wei Chen and Chieh-Chih Wang
2008 IEEE/RSJ International Conference on
Intelligent Robots and Systems (IROS)
Abstract |
Perceiving
human faces is one of the most important functions for human robot
interaction. The active appearance model (AAM) is a statistical
approach that models the shape and texture of a target object.
According to a number of the existing works, AAM has a great success in
modeling human faces. Unfortunately, the traditional AAM framework
could fail when the face pose changes as only 2D information is used to
model a 3D object. To overcome this limitation, we propose a 3D AAM
framework in which a 3D shape model and an appearance model are used to
model human faces. Instead of choosing a proper weighting constant to
balance the contributions from appearance similarity and the constraint
on consistent 2D shape with 3D shape in the existing work, our approach
directly matches 2D visual faces with the 3D shape model. No balancing
weighting between 2D shape and 3D shape is needed. In addition, only
frontal faces are needed for training and non-frontal faces can be
aligned successfully. The experimental results with 20 subjects
demonstrate the effectiveness of the proposed approach.
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Download |
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The full paper is available in PDF.
The video is available here.
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Bibtex |
@inproceedings{Chen_iros08,
author = {Chun-Wei Chen and Chieh-Chih Wang },
title = {3D Active Appearance
Model for Aligning Faces in 2D Images},
booktitle = {IEEE/RSJ
International Conference on Robots and Systems (IROS)},
address = {Nice, France},
month = {September},
year = {2008},
}
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Copyright ©
Chieh-Chih
(Bob) Wang 2008. All right reserved.
Last Updated: July 9, 2008.
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