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Face Alignment Using Active Shape Model And Support Vector Machine
Le Hoang Thai, Vo Nhat Truong
Pages - 224 - 234     |    Revised - 31-01-2011     |    Published - 08-02-2011
Volume - 4   Issue - 6    |    Publication Date - February  Table of Contents
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KEYWORDS
Face Alignment, Active Shape Model, Principal Component Analysis
ABSTRACT
The Active Shape Model (ASM) is one of the most popular local texture models for face alignment. It applies in many fields such as locating facial features in the image, face synthesis, etc. However, the experimental results show that the accuracy of the classical ASM for some applications is not high. This paper suggests some improvements on the classical ASM to increase the performance of the model in the application: face alignment. Four of our major improvements include: i) building a model combining Sobel filter and the 2-D profile in searching face in image; ii) applying Canny algorithm for the enhancement edge on image; iii) Support Vector Machine (SVM) is used to classify landmarks on face, in order to determine exactly location of these landmarks support for ASM; iv) automatically adjust 2-D profile in the multi-level model based on the size of the input image. The experimental results on CalTech face database and Technical University of Denmark database (imm_face) show that our proposed improvement leads to far better performance.
CITED BY (1)  
1 Suresh, K., & Chellappan, C. Overview and Comparative Analysis of Human Face Detection Overview and Comparative Analysis of Human Face Detection.
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Dr. Le Hoang Thai
Faculty of Information Technology, HoChiMinh University of Sciences, Vietnam - Vietnam
lhthai@fit.hcmus.edu.vn
Mr. Vo Nhat Truong
- Vietnam