Earticle

초록

영어

A human facial expression is the formation of facial muscle movement. In our previous research, we proposed a method of identifying facial muscle movement which based on motion templates and GentleBoost. But the method was not robust enough to recognize human expression due to insufficient learning stage. So in this paper, we proposed a new method based on motion templates and 4-layer deep learning neural network to identify human's facial expressions. We recognized Action Unit as a kind of features by using motion templates and adaboost firstly, and then the extracted features were used to feed a 4-layer deep learning neural network to recognize the facial expression. The experimental results have proved that the proposed method can solve the problem encountered in our previous research.

목차

Abstract
 1. Introduction
 2. Methodology
  2.1. Motion Templates
  2.2. Deep Learning Neural Network
 3. The Proposed Approach
  3.1. Input of the Network
  3.2. Structure of Network
 4. Results
  4.1. Training Set
  4.2. Experimental Results
 5. Discussion and Conclusion
 Reference

키워드

저자

• Jianzheng Liu [ College of Computer Science and Information Engineering Tianjin University of Science & Technology, Tianjin, China ]
• Xiaojing Wang [ College of Computer Science and Information Engineering Tianjin University of Science & Technology, Tianjin, China ]
• Jucheng Yang [ College of Computer Science and Information Engineering Tianjin University of Science & Technology, Tianjin, China ]
• Chao Wu [ College of Computer Science and Information Engineering Tianjin University of Science & Technology, Tianjin, China ]
• Lijun Liu [ Wuhan TipDM Intelligent Technology, No.999, Gaoxin Road, Wuhan, 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