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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3S39KCL
Repositorysid.inpe.br/sibgrapi/2018/10.16.17.36
Last Update2018:10.16.17.36.59 (UTC) gustavowl@lcc.ufrn.br
Metadata Repositorysid.inpe.br/sibgrapi/2018/10.16.17.36.59
Metadata Last Update2022:05.18.22.18.31 (UTC) administrator
Citation KeyBezerraGome:2018:ReOcLa
TitleRecognition of occluded and lateral faces using MTCNN, Dlib and homographies
FormatOn-line
Year2018
Access Date2024, Apr. 29
Number of Files1
Size1307 KiB
2. Context
Author1 Bezerra, Gustavo Alves
2 Gomes, Rafael Beserra
Affiliation1 Universidade Federal do Rio Grande do Norte
2 Universidade Federal do Rio Grande do Norte
EditorRoss, Arun
Gastal, Eduardo S. L.
Jorge, Joaquim A.
Queiroz, Ricardo L. de
Minetto, Rodrigo
Sarkar, Sudeep
Papa, João Paulo
Oliveira, Manuel M.
Arbeláez, Pablo
Mery, Domingo
Oliveira, Maria Cristina Ferreira de
Spina, Thiago Vallin
Mendes, Caroline Mazetto
Costa, Henrique Sérgio Gutierrez
Mejail, Marta Estela
Geus, Klaus de
Scheer, Sergio
e-Mail Addressgustavowl@lcc.ufrn.br
Conference NameConference on Graphics, Patterns and Images, 31 (SIBGRAPI)
Conference LocationFoz do Iguaçu, PR, Brazil
Date29 Oct.-1 Nov. 2018
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeUndergraduate Work
History (UTC)2018-10-16 17:36:59 :: gustavowl@lcc.ufrn.br -> administrator ::
2022-05-18 22:18:31 :: administrator -> :: 2018
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsface recognition
occlusion
homography
AbstractWith the advance of technology it is possible to create more robust security systems. For this task, image processing alongside Deep Neural Networks are currently being used in several works for facial recognition. However, occlusions and faces in different angles are a challenge for most algorithms. Attempting to contour this issue, an algorithm for facial recognition combining MTCNN, DLIB and homographies is proposed. In the obtained results, a comparison between the proposed algorithm and basis works indicates that, for some controlled cases, a mean accuracy improvement of 7.4% was obtained, with a maximum of 8.23% for occluded faces and 14.08% for lateral faces.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2018 > Recognition of occluded...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3S39KCL
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3S39KCL
Languageen
Target FileRecognition_of_Occluded_and_Lateral_Faces.pdf
User Groupgustavowl@lcc.ufrn.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3RPADUS
Citing Item Listsid.inpe.br/sibgrapi/2018/09.03.20.37 9
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy 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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