1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 8JMKD3MGPAW/3M9LKLL |
Repository | sid.inpe.br/sibgrapi/2016/08.16.18.30 |
Last Update | 2016:08.16.18.30.22 (UTC) administrator |
Metadata Repository | sid.inpe.br/sibgrapi/2016/08.16.18.30.22 |
Metadata Last Update | 2022:05.18.22.21.08 (UTC) administrator |
Citation Key | FilisbinoGiraThom:2016:TeFiMu |
Title | Tensor Fields for Multilinear Image Representation and Statistical Learning Models Applications |
Format | On-line |
Year | 2016 |
Access Date | 2024, May 03 |
Number of Files | 1 |
Size | 1868 KiB |
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2. Context | |
Author | 1 Filisbino, Tiene André 2 Giraldi, Gilson Antonio 3 Thomaz, Carlos Eduardo |
Affiliation | 1 National Laboratory for Scientific Computing 2 National Laboratory for Scientific Computing 3 Department of Electrical Engineering, FEI |
Editor | Aliaga, Daniel G. Davis, Larry S. Farias, Ricardo C. Fernandes, Leandro A. F. Gibson, Stuart J. Giraldi, Gilson A. Gois, João Paulo Maciel, Anderson Menotti, David Miranda, Paulo A. V. Musse, Soraia Namikawa, Laercio Pamplona, Mauricio Papa, João Paulo Santos, Jefersson dos Schwartz, William Robson Thomaz, Carlos E. |
e-Mail Address | gilson@lncc.br |
Conference Name | Conference on Graphics, Patterns and Images, 29 (SIBGRAPI) |
Conference Location | São José dos Campos, SP, Brazil |
Date | 4-7 Oct. 2016 |
Publisher | Sociedade Brasileira de Computação |
Publisher City | Porto Alegre |
Book Title | Proceedings |
Tertiary Type | Tutorial |
History (UTC) | 2016-08-16 18:30:22 :: gilson@lncc.br -> administrator :: 2022-05-18 22:21:08 :: administrator -> :: 2016 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Keywords | Tensor Fields Dimensionality Reduction Tensor Subspace Learning Ranking Tensor Components Reconstruction MPCA Face Image Analysis |
Abstract | Nowadays, higher order tensors have been applied to model multidimensional image data for subsequent tensor decomposition, dimensionality reduction and classification tasks. In this paper, we survey recent results with the goal of highlighting the power of tensor methods as a general technique for data representation, their advantage if compared with vector counterparts and some research challenges. Hence, we firstly review the geometric theory behind tensor fields and their algebraic representation. Afterwards, subspace learning, dimensionality reduction, discriminant analysis and reconstruction problems are considered following the traditional viewpoint for tensor fields in image processing, based on generalized matrices. We show several experimental results to point out the effectiveness of multilinear algorithms for dimensionality reduction combined with discriminant techniques for selecting tensor components for face image analysis, considering gender classification as well as reconstruction problems. Then, we return to the geometric approach for tensors and discuss opened issues in this area related to manifold learning and tensor fields, incorporation of prior information and high performance computational requirements. Finally, we offer conclusions and final remarks. |
Arrangement | urlib.net > SDLA > Fonds > SIBGRAPI 2016 > Tensor Fields for... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | |
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4. Conditions of access and use | |
data URL | http://urlib.net/ibi/8JMKD3MGPAW/3M9LKLL |
zipped data URL | http://urlib.net/zip/8JMKD3MGPAW/3M9LKLL |
Language | en |
Target File | Survey-Paper-Tutorial-Sib-19-07-2016.pdf |
User Group | gilson@lncc.br |
Visibility | shown |
Update Permission | not transferred |
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5. Allied materials | |
Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 |
Next Higher Units | 8JMKD3MGPAW/3M2D4LP |
Citing Item List | sid.inpe.br/sibgrapi/2016/07.02.23.50 5 sid.inpe.br/banon/2001/03.30.15.38.24 1 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notes | |
Empty Fields | archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume |
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