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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/3U56U6E
Repositorysid.inpe.br/sibgrapi/2019/09.25.13.50
Last Update2019:09.25.13.50.48 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2019/09.25.13.50.48
Metadata Last Update2022:06.14.00.09.43 (UTC) administrator
DOI10.1109/SIBGRAPI.2019.00032
Citation KeyLucioLarZanMorMen:2019:SiIrPe
TitleSimultaneous Iris and Periocular Region Detection Using Coarse Annotations
FormatOn-line
Year2019
Access Date2024, Apr. 27
Number of Files1
Size980 KiB
2. Context
Author1 Lucio, Diego Rafael
2 Laroca, Rayson
3 Zanlorensi, Luiz Antonio
4 Moreira, Gladston
5 Menotti, David
Affiliation1 Federal University of Paraná
2 Federal University of Paraná
3 Federal University of Paraná
4 Federal University of Ouro Preto
5 Federal University of Paraná
EditorOliveira, Luciano Rebouças de
Sarder, Pinaki
Lage, Marcos
Sadlo, Filip
e-Mail Addressdiegorafaellucio@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)2019-09-25 13:54:27 :: diegorafaellucio@gmail.com -> administrator :: 2019
2022-06-14 00:09:43 :: administrator -> diegorafaellucio@gmail.com :: 2019
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsiris
periocular
detection
simultaneous
AbstractIn this work, we propose to detect the iris and periocular regions simultaneously using coarse annotations and two well-known object detectors: YOLOv2 and Faster R-CNN. We believe coarse annotations can be used in recognition systems based on the iris and periocular regions, given the much smaller engineering effort required to manually annotate the training images. We manually made coarse annotations of the iris and periocular regions (~ 122K images from the visible (VIS) spectrum and ~ 38K images from the near-infrared (NIR) spectrum). The iris annotations in the NIR databases were generated semi-automatically by first applying an iris segmentation CNN and then performing a manual inspection. These annotations were made for 11 well-known public databases (3 NIR and 8 VIS) designed for the iris-based recognition problem, and are publicly available to the research community1. Experimenting our proposal on these databases, we highlight two results. First, the Faster R-CNN + Feature Pyramid Network (FPN) model reported an Intersection over Union (IoU) higher than YOLOv2 (91.86% vs 85.30%). Second, the detection of the iris and periocular regions being performed simultaneously is as accurate as performed separately, but with a lower computational cost, i.e. two tasks were carried out at the cost of one.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2019 > Simultaneous Iris and...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Simultaneous Iris and...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/3U56U6E
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/3U56U6E
Languageen
Target File2019_SIBGRAPI_IRIS_PRD_Detection.pdf
User Groupdiegorafaellucio@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)diegorafaellucio@gmail.com
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