Facial Expression Recognition From Image Sequence Based on LBP and Taylor Expansion

doi:10.1109/ACCESS.2017.2737821

	Facial Expression Recognition From Image Sequence Based on LBP and Taylor Expansion
	Ding, Yuanyuan 1,2; Zhao, Qin 1,2; Li, Baoqing 1; Yuan, Xiaobing 1
	2017
发表期刊	IEEE ACCESS
ISSN	2169-3536
卷号	5 页码:19409-19419
摘要	The aim of an automatic video-based facial expression recognition system is to detect and classify human facial expressions from image sequence. An integrated automatic system often involves two components: 1) peak expression frame detection and 2) expression feature extraction. In comparison with the image-based expression recognition system, the video-based recognition system often performs online detection, which prefers low-dimensional feature representation for cost-effectiveness. Moreover, effective feature extraction is needed for classification. Many recent recognition systems often incorporate rich additional subjective information and thus become less efficient for real-time application. In our facial expression recognition system, first, we propose the double local binary pattern (DLBP) to detect the peak expression frame from the video. The proposed DLBP method has a much lower-dimensional size and can successfully reduce detection time. Besides, to handle the illumination variations in LBP, logarithm-laplace (LL) domain is further proposed to get a more robust facial feature for detection. Finally, the Taylor expansion theorem is employed in our system for the first time to extract facial expression feature. We propose the Taylor feature pattern (TFP) based on the LBP and Taylor expansion to obtain an effective facial feature from the Taylor feature map. Experimental results on the JAFFE and Cohn-Kanade data sets show that the proposed TFP method outperforms some state-of-the-art LBP-based feature extraction methods for facial expression feature extraction and can be suited for real-time applications.
关键词	Pattern recognition facial expression recognition video processing image processing
DOI	10.1109/ACCESS.2017.2737821
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000412776800017
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：56[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/6866
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Li, Baoqing
作者单位	1.Chinese Acad Sci, Shanghai Inst Microsyst & Informat Technol, Wireless Sensor Network Lab, Shanghai 201800, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Ding, Yuanyuan,Zhao, Qin,Li, Baoqing,et al. Facial Expression Recognition From Image Sequence Based on LBP and Taylor Expansion[J]. IEEE ACCESS,2017,5:19409-19419.
APA	Ding, Yuanyuan,Zhao, Qin,Li, Baoqing,&Yuan, Xiaobing.(2017).Facial Expression Recognition From Image Sequence Based on LBP and Taylor Expansion.IEEE ACCESS,5,19409-19419.
MLA	Ding, Yuanyuan,et al."Facial Expression Recognition From Image Sequence Based on LBP and Taylor Expansion".IEEE ACCESS 5(2017):19409-19419.