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Edge-based effective active appearance model for real-time wrinkle detection.

Umirzakova Sabina1, Taeg Keun Whangbo2

  • 1Department of IT Convergence Engineering, Gachon University, Seongnam, South Korea.

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Summary

This study introduces an effective algorithm for detecting nasolabial wrinkles using the Active Appearance Model and Hessian filter. The method successfully tracks complex wrinkle lines, improving facial feature analysis.

Keywords:
active appearance modelautomatic wrinkle detectionface feature pointsface landmark detectionfacial wrinklesnasolabial wrinkle line

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Area of Science:

  • Computer Vision
  • Biomedical Image Analysis

Background:

  • Facial feature analysis, particularly wrinkles, is crucial for applications like age estimation and expression recognition.
  • Wrinkles are key indicators in facial analysis, with significant research interest and diverse applications.
  • Existing methods often focus on simpler, linear wrinkles, overlooking complex facial lines.

Purpose of the Study:

  • To develop an effective algorithm for detecting nasolabial wrinkles, which are complex and varied in shape.
  • To address limitations in current image-based wrinkle analysis, especially for non-linear facial lines.
  • To improve the accuracy and robustness of wrinkle detection in facial images.

Main Methods:

  • Utilized an Active Appearance Model (AAM) combined with a Hessian filter for nasolabial wrinkle detection.
  • Developed a novel approach to generate unique initial shapes for wrinkle lines, enhancing localization accuracy.
  • Implemented an algorithm specifically designed for curvilinear discontinuity analysis in facial images.

Main Results:

  • The proposed method effectively tracks and detects complexly structured nasolabial wrinkle lines.
  • Experimental results demonstrate the algorithm's capability in handling the variety of shapes found in nasolabial wrinkles.
  • The method shows competitive performance in detecting challenging nasolabial wrinkle patterns.

Conclusions:

  • The study highlights the effectiveness of modifying the Active Appearance Model structure for wrinkle line localization.
  • The proposed wrinkle detection method achieves competitive results in identifying nasolabial wrinkles.
  • This research contributes a robust algorithm for analyzing complex facial wrinkles.