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Facial Feature Point Extraction Using the Adaptive Mean Shape in Active Shape Model.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Rangan, C. Pandu
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Gagalowicz, André
Philips, Wilfried
Hyun-Chul Kim
Hyoung-Joon Kim
Wonjun Hwang
Source :
Computer Vision/Computer Graphics Collaboration Techniques; 2007, p421-429, 9p
Publication Year :
2007

Abstract

The fixed mean shape that is built from the statistical shape model produces an erroneous feature extraction result when ASM is applied to multi-pose faces. To remedy this problem the mean shape vector which is similar to an input face image is needed. In this paper, we propose the adaptive mean shape to extract facial features accurately for non frontal face. It indicates the mean shape vector that is the most similar to the face form of the input image. Our experimental results show that the proposed method obtains feature point positions with high accuracy and significantly improving the performance of facial feature extraction over and above that of the original ASM. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540714569
Database :
Supplemental Index
Journal :
Computer Vision/Computer Graphics Collaboration Techniques
Publication Type :
Book
Accession number :
33180246
Full Text :
https://doi.org/10.1007/978-3-540-71457-6_38