Facial Feature Localization Using Robust Active Shape Model and POEM Descriptors

2014 ◽  
Vol 9 (3) ◽  
Author(s):  
Lifang Zhou ◽  
Bin Fang ◽  
Weisheng Li ◽  
Lai Peng
Keyword(s):  
Facial Feature ◽  
Active Shape Model ◽  
Shape Model ◽  
Facial Feature Localization ◽  
Active Shape ◽  
Feature Localization

Real time facial feature localization based on improved active shape model

2012 ◽  
Author(s):  
Fan Zhang ◽  
Ruimin Shen ◽  
Lishuang Xu ◽  
Gang Chen ◽  
Jiajun Wang
Keyword(s):  
Real Time ◽  
Facial Feature ◽  
Active Shape Model ◽  
Shape Model ◽  
Facial Feature Localization ◽  
Active Shape ◽  
Feature Localization

Facial feature localization based on an improved active shape model

2008 ◽  
Vol 178 (9) ◽  
pp. 2215-2223 ◽  
Author(s):  
Z ZHENG ◽  
J JIONG ◽  
D CHUNJIANG ◽  
X LIU ◽  
J YANG
Keyword(s):  
Facial Feature ◽  
Active Shape Model ◽  
Shape Model ◽  
Facial Feature Localization ◽  
Active Shape ◽  
Feature Localization

scholarly journals An Improved Active Shape Model Application on Facial Feature Localization

2010 ◽  
Vol 2 (1) ◽  
pp. 1-9
Author(s):  
Min Wang ◽  
Yiling Wen ◽  
Li Fang ◽  
Weiping Sun
Keyword(s):  
Facial Feature ◽  
Active Shape Model ◽  
Shape Model ◽  
Model Application ◽  
Facial Feature Localization ◽  
Active Shape ◽  
Feature Localization

NEW FACIAL FEATURE LOCALIZATION ALGORITHM USING ADAPTIVE ACTIVE SHAPE MODEL

2012 ◽  
Vol 26 (01) ◽  
pp. 1256003 ◽  
Author(s):  
ROGHAYEH ALEMY ◽  
MOHAMMAD EBRAHIM SHIRI ◽  
FARZAD DIDEHVAR ◽  
ZEYNAB HAJIMOHAMMADI
Keyword(s):  
Facial Feature ◽  
Active Shape Model ◽  
Localization Algorithm ◽  
Shape Model ◽  
Localization Accuracy ◽  
Facial Hair ◽  
Average Improvement ◽  
Facial Feature Localization ◽  
Active Shape ◽  
Feature Localization

One of the important steps in/towards face recognition is facial feature localization which is difficult. The variety of human faces, expressions, facial hair, race, glasses, poses, and lighting contribute to the complexity of the problem. We systematically varied some of these factors to test the performance of the original active shape model (ASM) and in the next step we modified original ASM that improved accuracy of ASM. Due to these modifications, a new scheme of active shape model for facial feature extraction is proposed in this paper which is named adaptive active shape model. In this scheme, the improvement of the performance of the original ASM focuses on the following three aspects. First, the profile of the original ASM is extended from 1D to 2D. Second, a new face model is constructed in three expressions (natural, smiling, and screaming). Third, in ASM search step, the expression of face is recognized, and the profile model of expression which extracted is used to localize landmark. An extensive experimental investigation is conducted using AR, FERET, JAFFE, YaleB, and Indian face databases. The average improvement of the landmark localization accuracy for proposed method in comparison to the original ASM, under different facial expressions, different illumination conditions, and race variations respectively are 1.85, 0.66 and 7.96.

Improved active shape model and its application to facial feature extraction

2013 ◽  
Vol 22 (3) ◽  
pp. 033023
Author(s):  
Dejun Tang ◽  
Weishi Zhang ◽  
Xiaolu Qu ◽  
Dongqing Zhang
Keyword(s):  
Feature Extraction ◽  
Facial Feature ◽  
Active Shape Model ◽  
Shape Model ◽  
Facial Feature Extraction ◽  
Active Shape
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