Facial expression recognition algorithm based on CNN and LBP feature fusion

doi:10.1145/3175603.3175615

CORC > 兰州理工大学 > 兰州理工大学

	Facial expression recognition algorithm based on CNN and LBP feature fusion
	Yang, Xinli; Li, Ming; Zhao, ShiLin
	2017-12-29
会议日期	December 29, 2017 - December 31, 2017
会议地点	Shanghai, China
关键词	Convolution Robotics Rotation Convolution neural network Expression recognition Facial expression recognition Facial Expressions Feature expression Feature fusion Local binary patterns Rotation invariance
DOI	10.1145/3175603.3175615
页码	33-38
英文摘要	When a complex scene such as rotation within a plane is encountered, the recognition rate of facial expressions will decrease much. A facial expression recognition algorithm based on CNN and LBP feature fusion is proposed in this paper. Firstly, according to the problem of the lack of feature expression ability of CNN in the process of expression recognition, a CNN model was designed. The model is composed of structural units that have two successive convolutional layers followed by a pool layer, which can improve the expressive ability of CNN. Then, the designed CNN model was used to extract the facial expression features, and local binary pattern (LBP) features with rotation invariance were fused. To a certain extent, it makes up for the lack of CNN sensitivity to in-plane rotation changes. The experimental results show that the proposed method improves the expression recognition rate under the condition of plane rotation to a certain extent and has better robustness. © 2017 Association for Computing Machinery.
会议录	ACM International Conference Proceeding Series
会议录出版者	Association for Computing Machinery, 2 Penn Plaza, Suite 701, New York, NY 10121-0701, United States
语种	英语
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/117984]
专题	兰州理工大学
作者单位	School of Computer and Communication, Lanzhou University of Technology, Gansu Lanzhou; 730050, China
推荐引用方式 GB/T 7714	Yang, Xinli,Li, Ming,Zhao, ShiLin. Facial expression recognition algorithm based on CNN and LBP feature fusion[C]. 见:. Shanghai, China. December 29, 2017 - December 31, 2017.