A facial expression recognition model based on HMM

Author

Xuefeng Jiang

Author_Institution

Sch. of Electron. & Inf. Eng, Shenzhen Polytech., Shenzhen, China

Volume

6

fYear

2011

fDate

12-14 Aug. 2011

Firstpage

3054

Lastpage

3057

Abstract

The most expressive way humans display emotions is through facial expressions, and the facial expression recognition has been widely used. Although so many researches are done, it is hard to find a practical application in the real world. The motion of the face is modeled by HMM as follows, first, according to the function of HMM in processing continuous dynamic signal and model recognition, and for the sample´s overlap and similarity in the sample space, Code-HMM was made up respectively; then, inducted KNN and some discrimination rules by analyzing the output result. A method based on code HMM+KNN is proposed to recognize the facial expression. The experimental results show that this method is better than traditional HMM.

Keywords

emotion recognition; face recognition; hidden Markov models; learning (artificial intelligence); pattern classification; code HMM+KNN; code-HMM; continuous dynamic model recognition; continuous dynamic signal recognition; discrimination rules; facial expression recognition model; hidden Markov model; inducted KNN; k-nearest neighbor; Classification algorithms; Encoding; Face recognition; Hidden Markov models; Markov processes; Speech recognition; Training; HMM; code-hidden markov model(C-HMM); facial expression recognition; k-nearest Neighbor;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on

Conference_Location

Harbin, Heilongjiang, China

Print_ISBN

978-1-61284-087-1

Type

conf

DOI

10.1109/EMEIT.2011.6023733

Filename

6023733