基于差分能量图和CGBP的微表情识别

于明; 王英资; 于洋; 刘依

doi:10.3969/j.issn.0258-2724.2016.06.024

基于差分能量图和CGBP的微表情识别

doi: 10.3969/j.issn.0258-2724.2016.06.024

于明¹,
王英资^1,2,
于洋¹,
刘依¹

基金项目:

国家自然科学基金资助项目（60302018）

天津市科技计划资助项目（14RCGFGX00846）

河北省自然科学基金资助项目（F2015202239）

详细信息

作者简介:
于明(1964-),男,教授,博士,研究方向为图像处理与模式识别、智能媒体接口及生物信息识别,E-mail:yuming@hebut.edu.cn

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- 文章访问数: 498
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- PDF下载量: 191
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出版历程
- 收稿日期: 2015-05-20
- 刊出日期: 2016-12-25

Micro-expression Recognition Based on Differential Energy Maps and CGBP

摘要

摘要: 微表情是一种不能自主控制和伪装的面部表情，其与诚信度的关系密切，具有持续时间短且难以识别的特征.为提高计算机自动识别微表情的准确性，提出一种基于差分能量图和中心化Gabor二值模式（centralized Gabor binary patterns，CGBP）的微表情识别方法.该方法首先利用差分法计算微表情序列的能量得到差分能量图，获得人脸面部肌肉相位的变化；其次将Gabor与中心二值模式CBP相结合，得到CGBP算子对能量图进行微表情的特征提取；最后利用ELM分类器进行微表情分类识别.在CASME微表情库上的实验结果表明，该方法比LBP-TOP、DTSA3、Gabor、VLBP、CBP-TOP算法更能有效地获得微表情序列的时空纹理特征，平均识别率为86.54%.
- 图像处理 /
- 微表情识别 /
- 差分能量图 /
- 中心化Gabor二值化模式 /
- ELM分类器
Abstract: Micro-expression is a kind of facial expression which is autonomous and cannot be disguised. It has a close relation with credibility. Moreover,it has only a short duration and hard to be recognized. A micro-expression recognition algorithm based on the differential energy maps and centralized Gabor binary patterns (CGBP) was presented. Firstly, this algorithm uses the difference among micro-expression sequence images to calculate the energy maps and obtain the phase changes of facial muscle. Secondly, CGBP operators that combines Gabor and centralized binary patterns was proposed to extract micro-expression features. Finally, ELM classifier was used to classify micro-expressions. Experimental results on CASME micro-expression database show that compared with the state-of-the-art LBP-TOP, DTSA3, Gabor, VLBP, and CBP-TOP algorithms, this proposed method can obtain better spatial and temporal texture features and achieve higher recognition rate, which reaches 86.54% averagely.
- image processing /
- micro-expressions recognition /
- difference energy image /
- centralized Gabor binary patterns /
- extreme learning machine (ELM) classifier

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参考文献(20)

贲晛烨,杨明强,张鹏,等. 微表情自动识别综述[J]. 计算机辅助设计与图形学学报,2014,26(9):1385-1395. BEN Xianye, YANG Mingqiang, ZHANG Peng, et al. Survey on automatic micro expression recognition methods[J]. Journal of Computer-Aided Design Computer Graphics, 2014, 26(9):1385-1395.

YAN W J, WANG S J, LIU Y J, et al. For micro-expression recognition:database and suggestions[J]. Neurocomputing, 2014, 136:82-87.

EKMAN P. Telling lies:clues to deceit in the marketplace, politics, and marriage[M]. Revised Edition. New York:WW Norton Company, 2009:123-161.

EKMAN P. Lie catching and microexpressions:the philosophy of deception[M]. Oxford:Oxford University Press, 2009:118-133.

POLIKOVSKY S, KAMEDA Y, OHTA Y. Facial micro-expressions recognition using high speed camera and 3D-gradient descriptor[C]//3rd International Conference on Imaging for Crime Detection and Prevention(ICDP 2009). London:IEEE Computer Society Press, 2009:1-6.

SHREVE M, GODAVARTHY S, GOLDGOF D, et al. Macro-and micro-expression spotting in long videos using spatio-temporal strain[C]//2011 IEEE International Conference on Automatic Face Gesture Recognition and Workshops (FG 2011). Santa Barbara:IEEE Computer Society Press, 2011:51-56.

FRANK M G, HERBASZ M, SINUK K, et al. I see how you feel:training laypeople and professionals to recognize fleeting emotions[C]//The Annual Meeting of the International Communication Association. New York:, 2009:1-35.

于明,胡全胜,阎刚,等. 基于LGBP特征和稀疏表示的人脸表情识别[J]. 计算机工程与设计,2013,34(5):1787-1791. YU Ming, HU Quansheng, YAN Gang, et al. Facial expression recognition based on LGBP features and sparse representation[J]. Computer Engineering and Design, 2013, 34(5):1787-1791.

EKMAN P, FRIESEN W V. Nonverbal leakage and clues to deception[J]. Psychiatry, 1969, 32(1):88-106.

PORTER S, BRINKE L. The truth about lies:what works in detecting high-stakes deception?[J]. Legal and Criminological Psychology, 2010, 15(1):57-75.

SHREVE M, GODAVARTHY S, MANOHAR V, et al. Towards macro-and micro-expression spotting in video using strain patterns[C]//2009 Workshop on Applications of Computer Vision (WACV). Snowbird:IEEE Computer Society Press, 2009:1-6.

PFISTER T, LI X, ZHAO G, et al. Recognising spontaneous facial micro-expressions[C]//Proceedings of IEEE International Conference on Computer Vision (ICCV). Barcelona:IEEE Computer Society Press, 2011:1449-1456.

WU Q, SHEN X, FU X. The machine knows what you are hiding:an automatic micro-expression recognition system[C]//Affective Computing and Intelligent Interaction. Berlin:Springer Berlin Heidelberg, 2011:152-162.

YAN W J, WU Q, LIU Y J, et al. CASME database:a dataset of spontaneous micro-expressions collected from neutralized faces[C]//Proceedings of the 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition(FG). Shanghai:IEEE Computer Society Press, 2013:1-7.

BASHIR K, XIANG T, GONG S. Feature selection on gait energy image for human identification[C]//Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing.:IEEE, 2008:985-988.

吴奇,申寻兵,傅小兰. 微表情研究及其应用[J]. 心理科学进展,2010,18(9):1359-1368. WU Qi, SHEN Xunbing, FU Xiaolan. The research and application of micro-exprsion[J]. Advances in Psychological Science, 2010, 18(9):1359-1368.

FU X, WEI W. Centralized binary patterns embedded with image euclidean distance for facial expression recognition[C]//Proceedings of the Fourth International Conference on Natural Computation(ICNC'08). Jinan:IEEE Computer Society Press, 2008, 4:115-119.

YAN K, CHEN Y, ZHANG D. Gabor surface feature for face recognition[C]//Proceedings of First Asian Conference on Pattern Recognition (ACPR). Beijing:IEEE Computer Society Press, 2011:288-292.

RAVI J, TEVARAMANI S S, RAJA K B. Face recognition using DT-CWT and LBP features[C]//Proceedings of International Conference on Computing, Communication and Applications (ICCCA). Dindigul, Tamilnadu:IEEE Computer Society Press, 2012:1-6.

HUANG G B, ZHOU H, DING X, et al. Extreme learning machine for regression and multiclass classification[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B:Cybernetics, 2012, 42(2):513-529.

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文章访问数: 498
HTML全文浏览量: 60
PDF下载量: 191
被引次数: 0

基于差分能量图和CGBP的微表情识别

doi: 10.3969/j.issn.0258-2724.2016.06.024

作者简介: 于明(1964-),男,教授,博士,研究方向为图像处理与模式识别、智能媒体接口及生物信息识别,E-mail:yuming@hebut.edu.cn

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出版历程

Micro-expression Recognition Based on Differential Energy Maps and CGBP

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出版历程

目录

作者简介:
于明(1964-),男,教授,博士,研究方向为图像处理与模式识别、智能媒体接口及生物信息识别,E-mail:yuming@hebut.edu.cn