Close
Metadata

1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/3U36MAB
Repositorysid.inpe.br/sibgrapi/2019/09.13.05.12
Last Update2019:09.13.05.12.33 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2019/09.13.05.12.33
Metadata Last Update2022:06.14.00.09.39 (UTC) administrator
DOI10.1109/SIBGRAPI.2019.00030
Citation KeyCostaCoutCout:2019:FaReUs
TitleFace Recognition Using LBP on an Image Transformation Based on Complex Network Degrees
FormatOn-line
Year2019
Access Date2024, Apr. 27
Number of Files1
Size4621 KiB
2. Context
Author1 Costa, Murilo Villas Boas da
2 Couto, Cynthia Martins Villar
3 Couto, Leandro Nogueira
Affiliation1 Uberlandia Federal University
2 Sao Paulo University
3 Uberlandia Federal University
EditorOliveira, Luciano Rebouças de
Sarder, Pinaki
Lage, Marcos
Sadlo, Filip
e-Mail Addresslandovers@gmail.com
Conference NameConference on Graphics, Patterns and Images, 32 (SIBGRAPI)
Conference LocationRio de Janeiro, RJ, Brazil
Date28-31 Oct. 2019
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2019-09-13 05:12:33 :: landovers@gmail.com -> administrator ::
2022-06-14 00:09:39 :: administrator -> landovers@gmail.com :: 2019
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordstexture recognition
local binary patterns
complex networks
AbstractAutomated visual face recognition involves acquiring descriptive features from the image. Local Binary Patterns (LBP) is a powerful method to that end, capably characterizing local features. An crucial limitation of LBP, however, is that the feature vector's size becomes unmanageable when the method employed on even moderately large regions. In order to describe larger scale features, this work proposes a descriptor based on applying the LBP histogram applied to an image transformation based on node degree data derived from a complex network representation of the original image. The complex network generation heuristic and parameters are discussed. The complex network representation is shown to be able to condense larger scale image patterns into a local value that can be handled by LBP. LBP applied to this image transformation yields results that outperform LBP. We validate our proposed approach by applying our method to a face recognition task using three challenging databases. Results demonstrate that, for a large enough complex network generation radius, our method consistently outperforms LBP, while using a feature vector of the same size.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2019 > Face Recognition Using...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Face Recognition Using...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 13/09/2019 02:12 1.2 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/3U36MAB
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/3U36MAB
Languageen
Target FileFace_recognition_using_local_binary_patterns_on_an_image_transformation_based_on_complex_network_degrees___SIBGRAPI_2019.pdf
User Grouplandovers@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/3UA4FNL
8JMKD3MGPEW34M/3UA4FPS
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2019/10.25.18.30.33 1
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination 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 volume
7. Description control
e-Mail (login)landovers@gmail.com
update 


Close