PSYCH OpenIR  > 中国科学院行为科学重点实验室
Discriminative Spatiotemporal Local Binary Pattern with Revisited Integral Projection for Spontaneous Facial Micro-Expression Recognition
Huang, Xiaohua1,2; Wang, Su-Jing3,4; Liu, Xin5; Zhao, Guoying6; Feng, Xiaoyi7; Pietikainen, Matti5
First AuthorXiaohua Huang
2019
Source PublicationIEEE TRANSACTIONS ON AFFECTIVE COMPUTING
Correspondent Emailguoying.zhao@oulu.fi
ISSN1949-3045
SubtypeArticle
Volume10Issue:1Pages:32-47
Contribution Rank3
Abstract

Recently, there have been increasing interests in inferring mirco-expression from facial image sequences. Due to subtle facial movement of micro-expressions, feature extraction has become an important and critical issue for spontaneous facial micro-expression recognition. Recent works used spatiotemporal local binary pattern (STLBP) for micro-expression recognition and considered dynamic texture information to represent face images. However, they miss the shape attribute of face images. On the other hand, they extract the spatiotemporal features from the global face regions while ignore the discriminative information between two micro-expression classes. The above-mentioned problems seriously limit the application of STLBP to micro-expression recognition. In this paper, we propose a discriminative spatiotemporal local binary pattern based on an integral projection to resolve the problems of STLBP for micro-expression recognition. First, we revisit an integral projection for preserving the shape attribute of micro-expressions by using robust principal component analysis. Furthermore, a revisited integral projection is incorporated with local binary pattern across spatial and temporal domains. Specifically, we extract the novel spatiotemporal features incorporating shape attributes into spatiotemporal texture features. For increasing the discrimination of micro-expressions, we propose a new feature selection based on Laplacian method to extract the discriminative information for facial micro-expression recognition. Intensive experiments are conducted on three availably published micro-expression databases including CASME, CASME2 and SMIC databases. We compare our method with the state-of-the-art algorithms. Experimental results demonstrate that our proposed method achieves promising performance for micro-expression recognition.

KeywordSpontaneous facial micro-expression spatiotemporal local binary pattern integral projection feature selection
DOI10.1109/TAFFC.2017.2713359
Indexed BySCI
Language英语
Funding ProjectInfotech Oulu ; University of Oulu, Finland ; Tekes Fidipro Program ; Nokia Foundation ; Kaute Foundation ; Finnish Cultural Foundation ; Academy of Finland ; Beijing Natural Science Foundation[4152055] ; National Natural Science Foundation of China[61379095]
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000461333200006
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS KeywordOPTICAL-FLOW ; TEXTURE
Citation statistics
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/28805
Collection中国科学院行为科学重点实验室
Corresponding AuthorZhao, Guoying
Affiliation1.Nanjing Inst Technol, Sch Comp Engn, Nanjing 21167, Jiangsu, Peoples R China
2.Univ Oulu, FI-90014 Oulu, Finland
3.Inst Psychol, CAS Key Lab Behav Sci, Beijing 100101, Peoples R China
4.Univ Chinese Acad Sci, Dept Psychol, Beijing 100101, Peoples R China
5.Univ Oulu, Ctr Machine Vis & Signal Anal, FI-90014 Oulu, Finland
6.Northwest Univ, Sch Informat & Technol, Xian 710065, Shaanxi, Peoples R China
7.Northwestern Polytech Univ, Sch Elect & Informat, Xian 710065, Shaanxi, Peoples R China
Recommended Citation
GB/T 7714
Huang, Xiaohua,Wang, Su-Jing,Liu, Xin,et al. Discriminative Spatiotemporal Local Binary Pattern with Revisited Integral Projection for Spontaneous Facial Micro-Expression Recognition[J]. IEEE TRANSACTIONS ON AFFECTIVE COMPUTING,2019,10(1):32-47.
APA Huang, Xiaohua,Wang, Su-Jing,Liu, Xin,Zhao, Guoying,Feng, Xiaoyi,&Pietikainen, Matti.(2019).Discriminative Spatiotemporal Local Binary Pattern with Revisited Integral Projection for Spontaneous Facial Micro-Expression Recognition.IEEE TRANSACTIONS ON AFFECTIVE COMPUTING,10(1),32-47.
MLA Huang, Xiaohua,et al."Discriminative Spatiotemporal Local Binary Pattern with Revisited Integral Projection for Spontaneous Facial Micro-Expression Recognition".IEEE TRANSACTIONS ON AFFECTIVE COMPUTING 10.1(2019):32-47.
Files in This Item:
File Name/Size DocType Version Access License
Discriminative Spati(6341KB)期刊论文作者接受稿限制开放CC BY-NC-SAView Application Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Huang, Xiaohua]'s Articles
[Wang, Su-Jing]'s Articles
[Liu, Xin]'s Articles
Baidu academic
Similar articles in Baidu academic
[Huang, Xiaohua]'s Articles
[Wang, Su-Jing]'s Articles
[Liu, Xin]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Huang, Xiaohua]'s Articles
[Wang, Su-Jing]'s Articles
[Liu, Xin]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: Discriminative Spatiotemporal Local Binary Pattern with Revisited Integral Projection for Spontaneous Facial Micro-Expression Recognition.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.