NDLI: Efficient and robust facial feature point estimation using direct combined model

Content Provider	IEEE Xplore Digital Library
Author	Tu, Ching-Ting Lien, Jenn-Jier James
Copyright Year	2010
Description	Author affiliation: Robotics Laboratory, Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan, R.O.C. (Tu, Ching-Ting; Lien, Jenn-Jier James)
Abstract	An efficient facial feature point detection approach based on a direct combined model (DCM) algorithm is proposed in this study. DCM efficiently models the correlation between the facial feature points (i.e. the facial shape) and the input texture information (i.e. the facial image) in a single, combined eigenspace to preserve the significant components of their dependency. Then a DCM estimator is developed for estimating facial feature points from the input image, where the learned correlation is explicitly take into account. Previous proposals for estimating facial shapes are heavily reliant on the quality of the texture estimation results, which in turn are highly sensitive to occlusion and lighting effects in the input image. Experiments show that the DCM approach accurately estimates the facial shape without the need to restore the texture information lost as a result of unfavorable occlusion or lighting conditions.
Starting Page	4517
Ending Page	4520
File Size	575451
Page Count	4
File Format	PDF
ISBN	9781424479924
ISSN	15224880
e-ISBN	9781424479948
e-ISBN	9781424479931
DOI	10.1109/ICIP.2010.5653201
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-26
Publisher Place	Hong Kong
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Estimation Active appearance model Facial features Training Correlation Lighting AAM Image processing and computer vision Eigenface statistical image models
Content Type	Text
Resource Type	Article

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