Earticle

초록

영어

The prior knowledge of face scale and shape are introduced into active contour model for face contour segmentation. Based on the variance of each column about image and the gradient of variance, the face outline size and central coordinates are obtained. The level set functions of the collected shapes are used as training data, which are projected onto a low dimension subspace. The attribute reduction of training set by PCA method is approximated Gaussian distribution. A constructed shape prior model with facial personality traits is incorporated into variational level set model based on boundary and region to constrain the contour evolution process, and then model can be accurately evolved into the face boundary. Experimental results validate the efficiency of this method.

목차

Abstract
 1. Introduction
 2. The Novel Method Proposed in This Paper
  2.1. Left and Right Boundaries of Face
  2.2. Upper and Lower Boundaries of Face
  2.3. The Area of Face and Center Coordinates
 3. The Basic Concepts of Algorithm
  3.1. Obtaining the Sample Sets
  3.2. The Registration of the Shape Training Set
  3.3. The Level Set Expression of the Training Sample
  3.4. Using PAC to Establish a Prior Shape Model
 4. Level Set Method Based on Prior Information
  4.1. Prior Scale Information
  4.2. Level Set Model Based on Prior Shape
 5. Experimental Results and Analysis
  5.1. Experimental Results
  5.2. Experimental Analysis
 6. Conclusion
 Acknowledgements
 References

키워드

저자

• Ji Zhao [ School of Software Engineering University of Science and Technology Liaoning Anshan, China ]
• Huibin Wang [ School of Software Engineering University of Science and Technology Liaoning Anshan, China ]
• Wenge Huang [ School of Software Engineering University of Science and Technology Liaoning Anshan, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605