Title :
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
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;
Conference_Titel :
Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4799-7980-6
DOI :
10.1109/CSE.2014.318
