A New Facial Expression Recognition Method Based on Geometric Alignment and LBP Features

Author

Xun Wang ; Xingang Liu ; Lingyun Lu ; Zhixin Shen

Author_Institution

Dept. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China

fYear

2014

fDate

19-21 Dec. 2014

Firstpage

1734

Lastpage

1737

Abstract

Automatic facial expression recognition has been drawn many attentions in both computer vision and artificial intelligence (AI) for the past decades. Although much progress has been made, facial expression recognition (FER) is still a challenging and interesting problem. In this paper, we propose a new FER system, which uses the active shape mode (ASM) algorithm to align the faces, then extracts local binary patterns (LBP) features and uses support vector machine (SVM) classifier to predict the facial emotion. Experiments on the Jaffe database show that the proposed method has a promising performance and increases the recognition rate by 5.2% compared to the method using Gabor features.

Keywords

computational geometry; emotion recognition; face recognition; feature extraction; image classification; support vector machines; ASM algorithm; FER system; Jaffe database; LBP feature extraction; SVM classifier; active shape mode algorithm; automatic facial expression recognition method; face alignment; facial emotion prediction; geometric alignment; local binary pattern feature extraction; recognition rate; support vector machine classifier; Databases; Face recognition; Feature extraction; Shape; Support vector machines; Training; Vectors; Active shape mode; Facial expression recognition; Local binary patterns; Support vector machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4799-7980-6

Type

conf

DOI

10.1109/CSE.2014.318

Filename

7023829