作者: Zhen-Tao Liu , Gui-Tian Sui , Dan-Yun Li , Guan-Zheng Tan
DOI: 10.1109/CHICC.2015.7260233
关键词: Artificial intelligence 、 Feature extraction 、 Pattern recognition 、 Three-dimensional face recognition 、 Extreme learning machine 、 Computer science 、 Gabor filter 、 Dimension (vector space) 、 Support vector machine 、 Feature (machine learning) 、 Principal component analysis
摘要: A facial expression recognition method based on Extreme Learning Machine (ELM) is proposed, in which Gabor filter and two dimension principal components analysis (2DPCA) are used for the feature extraction. The proposal uses ELM as learning algorithm because of its less stringent optimization constraints than other algorithms such SVM. experiments performed using both Cohan-Kanade JAFFE databases, 94% rate dataset 95% achieved.