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Fusion Tensor Subspace Transformation Framework
Wang, Su-Jing1,2,3; Zhou, Chun-Guang2; Fu, Xiaolan1; Wang, SJ (reprint author), Chinese Acad Sci, Inst Psychol, State Key Lab Brain & Cognit Sci, Beijing 100101, Peoples R China.
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AbstractTensor subspace transformation, a commonly used subspace transformation technique, has gained more and more popularity over the past few years because many objects in the real world can be naturally represented as multidimensional arrays, i.e. tensors. For example, a RGB facial image can be represented as a three-dimensional array (or 3rd-order tensor). The first two dimensionalities (or modes) represent the facial spatial information and the third dimensionality (or mode) represents the color space information. Each mode of the tensor may express a different semantic meaning. Thus different transformation strategies should be applied to different modes of the tensor according to their semantic meanings to obtain the best performance. To the best of our knowledge, there are no existing tensor subspace transformation algorithm which implements different transformation strategies on different modes of a tensor accordingly. In this paper, we propose a fusion tensor subspace transformation framework, a novel idea where different transformation strategies are implemented on separate modes of a tensor. Under the framework, we propose the Fusion Tensor Color Space (FTCS) model for face recognition.
Subject AreaCognitive Neuroscience
2013
Language英语
Source PublicationPLOS ONE
ISSN1932-6203
Volume8Issue:7
Subtype期刊论文
URL查看原文
Indexed BySCI
Project Intro.This work was supported in part by grants from 973 Program (2011CB302201), the National Natural Science Foundation of China (61075042, 61175023), China Postdoctoral Science Foundation funded project (2012M520428) and the open project program (93K172013K04) of Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
WOS KeywordLOCALITY PRESERVING PROJECTIONS ; FACE RECOGNITION ; DISCRIMINANT-ANALYSIS ; COMPONENT ANALYSIS ; EIGENFACES ; PCA
WOS HeadingsScience & Technology
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000321271900003
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/10817
Collection脑与认知科学国家重点实验室
Corresponding AuthorWang, SJ (reprint author), Chinese Acad Sci, Inst Psychol, State Key Lab Brain & Cognit Sci, Beijing 100101, Peoples R China.
Affiliation1.Chinese Acad Sci, Inst Psychol, State Key Lab Brain & Cognit Sci, Beijing 100101, Peoples R China
2.Jilin Univ, Coll Comp Sci & Technol, Changchun 130023, Jilin, Peoples R China
3.Jilin Univ, Minist Educ, Key Lab Symbol Computat & Knowledge Engn, Changchun 130023, Jilin, Peoples R China
First Author Affilication脑与认知科学国家重点实验室
Recommended Citation
GB/T 7714
Wang, Su-Jing,Zhou, Chun-Guang,Fu, Xiaolan,et al. Fusion Tensor Subspace Transformation Framework[J]. PLOS ONE,2013,8(7).
APA Wang, Su-Jing,Zhou, Chun-Guang,Fu, Xiaolan,&Wang, SJ .(2013).Fusion Tensor Subspace Transformation Framework.PLOS ONE,8(7).
MLA Wang, Su-Jing,et al."Fusion Tensor Subspace Transformation Framework".PLOS ONE 8.7(2013).
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