Multi-view laplacian eigenmaps based on bag-of-neighbors for RGB-D human emotion recognition

doi:10.1016/j.ins.2019.08.035

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	Multi-view laplacian eigenmaps based on bag-of-neighbors for RGB-D human emotion recognition
	Liu, Shenglan 1,2; Guo, Shuai 1; Wang, Wei 2; Qiao, Hong3 ; Wang, Yang 1; Luo, Wenbo 4
发表期刊	INFORMATION SCIENCES
ISSN	0020-0255
	2020
卷号	509 页码:243-256
通讯作者	Luo, Wenbo(luowb@lnnu.edu.cn)
摘要	Human emotion recognition is an important direction in the fields of human-computer interaction and computer vision. However, most existing human emotion researches just focus on one view of the study objects. In this paper, we first introduce a RGB-D video-emotion dataset and a RGB-D face-emotion dataset for research, both of which are collected under psychological principles and methods. Then we propose a new supervised nonlinear multi-view laplacian eigenmaps (MvLE) approach and a multi-hidden-layer out-of-sample network (MHON) that can make full use of RGB view and Depth view of the two datasets. MvLE is employed to map the samples of both views from original spaces into a common subspace. As samples of RGB view and Depth view lie on different spaces, a new distance metric bag of neighbors (BON) introduced in MvLE can capture their similar distributions. Moreover, to adapt to large-scale applications, MHON is developed to get the low-dimensional representations of additional samples and predict their labels. MvLE and MHON can deal with the cases that RGB view and Depth view have different dimensions of original spaces, even different number of samples or categories. The experiment results indicate that the proposed methods achieve considerable improvement over some state-of-art methods. (C) 2019 Elsevier Inc. All rights reserved.
关键词	Human emotion recognition MvLE BON MHON RGB-D
DOI	10.1016/j.ins.2019.08.035
关键词[WOS]	EXTREME LEARNING-MACHINE ; DIMENSIONALITY REDUCTION ; EXPRESSIONS ; FACE
收录类别	SCI
语种	英语
资助项目	LiaoNing Revitalization Talents Program[XLYC1086006] ; Development of Science and Technology of Guangdong Province Special Fund Project Grants[2016B090910001] ; National Key Scientific Instrument and Equipment Development Project[61627808] ; National Natural Science Foundation of China[31871106] ; National Natural Science Foundation of China[91648205] ; National Natural Science Foundation of China[61602082] ; National Natural Science Foundation of China[61672130] ; National Key Research and Development Program of China[2017YFB1300200] ; National Key Research and Development Program of China[2017YFB1300200] ; National Natural Science Foundation of China[61672130] ; National Natural Science Foundation of China[61602082] ; National Natural Science Foundation of China[91648205] ; National Natural Science Foundation of China[31871106] ; National Key Scientific Instrument and Equipment Development Project[61627808] ; Development of Science and Technology of Guangdong Province Special Fund Project Grants[2016B090910001] ; LiaoNing Revitalization Talents Program[XLYC1086006]
项目资助者	National Key Research and Development Program of China ; National Natural Science Foundation of China ; National Key Scientific Instrument and Equipment Development Project ; Development of Science and Technology of Guangdong Province Special Fund Project Grants ; LiaoNing Revitalization Talents Program
WOS研究方向	Computer Science
WOS类目	Computer Science, Information Systems
WOS记录号	WOS:000494883700016
出版者	ELSEVIER SCIENCE INC
引用统计	被引频次：13[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/28869
专题	多模态人工智能系统全国重点实验室_机器人理论与应用
通讯作者	Luo, Wenbo
作者单位	1.Dalian Univ Technol, Sch Innovat & Entrepreneurship, Dalian 116024, Liaoning, Peoples R China 2.Dalian Univ Technol, Fac Elect Informat & Elect Engn, Dalian 116024, Liaoning, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 4.Liaoning Normal Univ, Res Ctr Brain & Cognit Neurosci, Dalian 116024, Liaoning, Peoples R China
推荐引用方式 GB/T 7714	Liu, Shenglan,Guo, Shuai,Wang, Wei,et al. Multi-view laplacian eigenmaps based on bag-of-neighbors for RGB-D human emotion recognition[J]. INFORMATION SCIENCES,2020,509:243-256.
APA	Liu, Shenglan,Guo, Shuai,Wang, Wei,Qiao, Hong,Wang, Yang,&Luo, Wenbo.(2020).Multi-view laplacian eigenmaps based on bag-of-neighbors for RGB-D human emotion recognition.INFORMATION SCIENCES,509,243-256.
MLA	Liu, Shenglan,et al."Multi-view laplacian eigenmaps based on bag-of-neighbors for RGB-D human emotion recognition".INFORMATION SCIENCES 509(2020):243-256.