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Enhance the Alignment Accuracy of Active Shape Models Using Elastic Graph Matching

  • Sanqiang Zhao
  • Wen Gao
  • Shiguang Shan
  • Baocai Yin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3072)

Abstract

Active Shape Model (ASM) is one of the most popular methods for image alignment. To improve its matching accuracy, in this paper, ASM searching method is combined with a simplified Elastic Bunch Graph Matching (EBGM) algorithm. Considering that EBGM is too time-consuming, landmarks are grouped into contour points and inner points, and inner points are further separated into several groups according to the distribution around salient features. For contour points, the original local derivative profile matching is exploited. While for every group of inner points, two pre-defined control points are searched by EBGM, and then used to adjust other points in the same group by using an affine transformation. Experimental results have shown that the proposed method greatly improves the alignment accuracy of ASM with only a little increase of time requirement since EBGM is only applied to a few control points.

Keywords

Control Point Affine Transformation Active Contour Model Contour Point Alignment Accuracy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Sanqiang Zhao
    • 1
    • 2
  • Wen Gao
    • 2
  • Shiguang Shan
    • 2
  • Baocai Yin
    • 1
  1. 1.Multimedia and Intelligent Software Technology Beijing Municipal Key LaboratoryBeijing University of TechnologyBeijingChina
  2. 2.ICT-ISVISION JDL for Face Recognition, Institute of Computing Technology, CASBeijingChina

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