Earticle

초록

영어

Facial expressions analysis is a vital part of the research in human-machine interaction. This chapter introduces an automatic recognition system for facial expression from a front view human face image. Obtaining an effective facial representation from initial face images is an essential phase for strong and efficient facial expression system. In this chapter we have developed a facial expression analysis system. Firstly we have tried to evaluate facial analysis base on Active shape model (ASM). In order to detect the face images, Adaboost classifier and Haar-Like feature has been adopted to achieve face detection and tracking. The ASM then has been automatically initiated in the detected face image. Then, discriminates and reliable facial feature points has been extracted applying ASM fitting technique. The geometric displacement among the projected ASM feature points coordinates and the mean shape of ASM were used to evaluate facial expression. Using support vector machine (SVM) classifier, the obtained results has reached a recognition rate of 93 %.

목차

Abstract
 1. Introduction
 2. Related Works
 3. Database
 4. Proposed Approach
  4.1. Face Detection & Image Pre-Processing
  4.2. Haar Features
  4.3. Active Shape Models (ASM)
 5. Active Shape Model fitting
  5.1. Facial Vertices Representation
 6. Conclusion
 References

키워드

저자

• Reda Shbib [ School of Engineering, University of Portsmouth, United Kingdom ]
• Shikun Zhou [ School of Engineering, University of Portsmouth, United Kingdom ]

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