一种边缘二进制码的表情识别方法

doi:10.3969/j.issn.1001-2400.2015.03.031

J4 ›› 2015, Vol. 42 ›› Issue (3): 186-191.doi: 10.3969/j.issn.1001-2400.2015.03.031

一种边缘二进制码的表情识别方法

冯晓毅1;赖阳明1;王文星2;崔少星3;彭进业3;蒋晓悦1

(1. 西北工业大学电子信息学院，陕西西安 710129；
2. 中国飞行试验研究院中航工业飞行仿真航空科技重点实验室，陕西西安 710089;
3. 西北大学信息科学与技术学院，陕西西安 710127)

收稿日期:2014-01-13 出版日期:2015-06-20 发布日期:2015-07-27
通讯作者: 冯晓毅
作者简介:冯晓毅(1969-)，女，教授，E-mail: fengxiao@nwpu.edu.cn．
基金资助:
国家自然科学基金资助项目(60875016, 61075014) ；航空科学基金资助项目(20131353015)

Facial expression recognition based on the binary code of edges

FENG Xiaoyi1;LAI Yangming1;WANG Wenxing2;CUI Shaoxing3;PENG Jinye3;JIANG Xiaoyu1

(1. School of Electronics and Information, Northwestern Polytechnical Univ., Xi'an 710129, China;
2. AVIC Aeronautical Science and Technology Key Lab. of Flight Simulation, CFTE, Xi'an 710089, China;
3. School of Information Science and Technology, Northwest Univ., Xi'an 710127, China)

Received:2014-01-13 Online:2015-06-20 Published:2015-07-27
Contact: FENG Xiaoyi

摘要/Abstract

摘要：

针对如何从图像中提取有效的表情特征来提高表情识别率的问题，提出了一种基于边缘二进制码的表情特征提取方法，用于表情识别．该方法首先对图像进行边缘检测，然后对边缘的局部结构进行二进制码描述作为表情特征，最后利用支持向量机进行表情分类．在JAFFE人脸表情数据库上，分别用该方法和传统的方法进行试验，结果表明，该方法可显著提高表情识别率．

关键词: 表情识别, 特征提取, 二值图像, 边缘检测

Abstract:

Facial expression recognition mainly involves face locating, feature extraction, and expression classification. However, extracting effective features of facial expressions from original face images is a vital step for improving facial expression recognition. In this paper, a binary code of edge method is proposed for extracting the expression feature, which is used for facial expression recognition. Firstly, the face image is processed by an edge detection operator. Then, the proposed binary code method is applied to describe the edge binary image as the expression feature. Finally, the SVM classifier is used for facial expression recognition. Experiments are performed on JAFFE facial expression database, and the results show that the proposed method achieves a higher recognition rate than the traditional method.

Key words: facial expression recognition, feature extraction, binary images, edge detection

中图分类号:

TP391

冯晓毅;赖阳明;王文星;崔少星;彭进业;蒋晓悦. 一种边缘二进制码的表情识别方法[J]. J4, 2015, 42(3): 186-191.

FENG Xiaoyi;LAI Yangming;WANG Wenxing;CUI Shaoxing;PENG Jinye;JIANG Xiaoyu. Facial expression recognition based on the binary code of edges[J]. J4, 2015, 42(3): 186-191.

参考文献

［1］ Youssif A A A, Asker W A A. Automatic Facial Expression Recognition System Based on Geometric and Appearance Features ［J］. Computer and Information Science, 2011, 4(2): 115-124.
［2］ Liu Weifeng, Song Caifeng, Wang Yanjiang, et al. Facial Expression Recognition Based on Gabor Features and Sparse Representation ［C］//IEEE Proceedings of 12 International Conference on Control, Automation, Robotics ＆ Vision. Piscataway: IEEE, 2012: 1402-1406.
［3］ Banerji S, Sinha A, Liu Chengjun. New Image Descriptors Based on Color, Texture, Shape and Wavelets for Object and Scene Image Classification ［J］. Neurocomputing, 2013, 117: 173-185.
［4］ Zalewski L, Gong Shaogang. Synthesis and Recognition of Facial Expressions in Virtual 3D Views ［C］//IEEE International Conference on Automatic Face and Gesture Recognition. Piscataway: IEEE, 2004: 493-498.
［5］ Shrinivasa N C L, Shekhar J S, Das P K, et al. Automatic Facial Expression Recognition Using Extended AR-LBP ［C］//Proceedings of 6th International Conference on Information Processing. Berlin: Springer, 2012: 244-252.
［6］ Zhang Shiqing, Zhao Xiaoming, Lei Bicheng. Facial Expression Recognition Based on Local Binary Patterns and Local Fisher Discriminant Analysis ［J］. Wseas Transactions on Signal Processing, 2012, 8(1): 21-31.
［7］ Shrinivasa N C L, Das P K, Nair S B. Asymmetric Region Local Binary Pattern Operator for Person-dependent Facial Expression Recognition ［C］//Proceedings of 2012 International Conference on Computing, Communication and Applications. Piscataway: IEEE, 2012: 1-5.
［8］ Chellappa R, Wilson C L, Sirohey S. Human and Machine Recognition of Faces: a Survey ［J］. Proceedings of the IEEE, 1995, 83(5): 705-741.
［9］ Ekman P, Friesen W V, Hager J C. Facial Action Coding System ［M］. 2nd ed. London: Weidenfeld and Nicolson, 2002.
［10］赵晖, 王志良, 刘瑶峰. 人脸活动单元自动识别研究综述［J］. 计算机辅助设计与图形学学报, 2010, 22(5): 894-903.
Zhao Hui, Wang Zhiliang, Liu Yaofeng. A Survey of Automatic Facial Action Units Recognition ［J］. Journal of Computer Aided-Design ＆ Computer Graphics, 2010, 22(5): 894-903.
［11］应自炉, 方谢燕. 基于局部二元模式的面部表情识别研究［J］.计算机工程与应用, 2009, 45(29): 180-183.
Ying Zilu, Fang Xieyan. Facial Expression Recognition Research Based on Local Binary Pattern ［J］. Computer Engineering and Applications, 2009, 45(29): 180-183.
［12］ Anand G, Ravi K D, Rahul G, et al. DGW-Canny: an Improvised Version of Canny Edge Detector ［C］//Proceedings of 2011 International Symposium on Intelligent Signal Processing and Communication Systems. Piscataway: IEEE, 2011:1-6.
［13］章为川, 水鹏朗, 徐国靖. 边缘线上各向异性高斯核信息熵的角点检测［J］. 西安电子科技大学学报, 2013, 40(4): 119-124.
Zhang Weichuan, Shui Penglang, Xu Guojing. Corner Detection via Anisotropic Gaussian Kernels Information Entropy on Edge Contours ［J］. Journal of Xidian University, 2013, 40(4): 119-124.
［14］ Song Jiatao, Chi Zheru, Liu Jilin, et al. Extraction of the Face Image Edges with Application to Expression Analysis ［C］//Proceedings of 8th International Conference on Control, Automation. Piscataway: IEEE, 2004: 804-809.
［15］ Wu H C, Lu Jiahong. Effective Distance Measure for Unusual Facial Expression Detection of Human Face Images ［C］//Proceedings of 2th International Symposium on Aware Computing. Piscataway: IEEE, 2010: 18-23.
［16］ Valstar M, Patras I, Pantic M. Facial Action Unit Detection Using Probabilistic Actively Learned Support Vector Machines on Tracked Facial Point Data ［C］//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2005: 76-84.

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一种边缘二进制码的表情识别方法

Facial expression recognition based on the binary code of edges

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