Earticle

초록

영어

With the information society, the level of modern high-speed development, in order to adapt to constantly improve the economic standard of living, people are facing the pressure and thus the greater the incidence of depression showed a rising trend. The facial expression recognition based on the data of Facereader6 software, application SVM algorithm facial expression data in patients with depression feature extraction classification. Therefore, the law face expression feature extraction in patients with depression, according to the input different facial expressions to identify facial expressions in patients with depression. Population will suffer from depression in intervention and prevention have significant social role and practical significance.

목차

Abstract
 1. Introduction
 2. Facereader6 Collection of Facial Expressions
 3. Depression Expression Feature Extraction
  3.1. Wavelet Transform Theory
  3.2. Expression Recognition
 4. Results Analysis
 5. Summary
 References

키워드

저자

• Wang Ju [ Changchun University, Changchun, China ]
• Hong Mei [ Changchun University, Changchun, China ]
• Nie Chunyan [ Changchun University, Changchun, China ]
• Pan Su [ Department of Orthopedics, the Second Hospital of Jilin University, Changchun, China ]
• Yang Yudan [ China-Japan Union Hospital, Jilin University, Changchun, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605