Paper Title:
Enhance ASM Based on DCT-SVM for Facial Feature Points Localization
  Abstract

Focused on the facial feature points localization, the enhance ASM algorithm based on modeling texture by the DCT-SVM is proposed. First, the statistical shape model is built. Then, some key feature points are selected and their texture models are built by the DCT-SVM. In the subsequent searching, the feature points are divided into two classes based on their reliability gained by DCT-SVM detector, by combining the reliable feature points to the shape constraint, the original shape can finally match to the target face. Experiments show the algorithm is robust to the expressions change and can better locate the features than the traditional ASM.

  Info
Periodical
Chapter
Chapter 2: Advanced Design Science (1)
Edited by
Dongye Sun, Wen-Pei Sung and Ran Chen
Pages
820-824
DOI
10.4028/www.scientific.net/AMM.121-126.820
Citation
Y. J. Fu, J. W. Li, R. X. Xiang, "Enhance ASM Based on DCT-SVM for Facial Feature Points Localization", Applied Mechanics and Materials, Vols. 121-126, pp. 820-824, 2012
Online since
October 2011
Export
Price
$32.00
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