Smile Recognition Based on Support Vector Machine and Local Binary Pattern

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 机器人学研究室

	Smile Recognition Based on Support Vector Machine and Local Binary Pattern
	Zhao YW(赵忆文)2 ; Zhao XG(赵新刚)2 ; Huang Z(黄钲)2,3; Song GL(宋国立)2 ; Han JD(韩建达)1,2
	2018
会议日期	July 19-23, 2018
会议地点	Tianjin, China
关键词	Local Binary Pattern Support Vector Machine Smile recognition Haar-like feature
页码	938-942
英文摘要	In this paper, a method combining Local Binary Pattern (LBP) and Support Vector Machine (SVM) for smile detection is proposed. The process of smile recognition is divided into 5 parts including input images, image enforcement, face detection, feature extraction and classification. Firstly, the face images are downloaded from the Japanese Female Facial Expression (JAFFE) Database, which is then followed by the process of the image enforcement and processing such as noise removing and image normalization. After this, the human face extraction algorithm based on the combination of Haar factures and cascading AdaBoost algorithm is used to segment the human face from the images. Furthermore, Local Binary Pattern (LBP) is applied to extract features from face images Finally, Support Vector Machine based on Sequential Minimum Optimization (SMO) algorithm is implemented to classify the input feature vectors into two categories-smiling images or not smiling image. The result shows that this method can get the accuracy of 88.1%.
源文献作者	IEEE Robotics & Automation Society
产权排序	1
会议录	Proceedings of 2018 IEEE 8th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems
会议录出版者	IEEE
会议录出版地	New York
语种	英语
ISBN号	978-1-5386-7056-9
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/23859]
专题	沈阳自动化研究所_机器人学研究室
通讯作者	Song GL(宋国立)
作者单位	1.College of Computer and Control Engineering, Nankai University, Tianjin, China 2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 3.University of Chinese Academy of Sciences, Beijing, China
推荐引用方式 GB/T 7714	Zhao YW,Zhao XG,Huang Z,et al. Smile Recognition Based on Support Vector Machine and Local Binary Pattern[C]. 见:. Tianjin, China. July 19-23, 2018.