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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZeBBx/w4mtv
Repositorysid.inpe.br/banon/2002/11.04.12.08
Last Update2002:11.04.02.00.00 (UTC) administrator
Metadata Repositorysid.inpe.br/banon/2002/11.04.12.09
Metadata Last Update2022:06.14.00.12.00 (UTC) administrator
DOI10.1109/SIBGRA.2000.883891
Citation KeyCamposFeriCesa:2000:ImFaTi
TitleImproved face/spl times/non-face discrimination using Fourier descriptors through feature selection
Year2000
Access Date2024, May 04
Number of Files1
Size729 KiB
2. Context
Author1 Campos, Teófilo Emídio de
2 Feris, Rogério Schimidt
3 Cesar Junior, Roberto Marcondes
EditorCarvalho, Paulo Cezar Pinto
Walter, Marcelo
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 13 (SIBGRAPI)
Conference LocationGramado, RS, Brazil
Date17-20 Oct. 2000
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Pages28-35
Book TitleProceedings
Tertiary TypeFull Paper
OrganizationSBC - Brazilian Computer Society
History (UTC)2008-07-17 14:10:49 :: administrator -> banon ::
2008-08-26 15:23:00 :: banon -> administrator ::
2009-08-13 20:36:50 :: administrator -> banon ::
2010-08-28 20:00:08 :: banon -> administrator ::
2022-06-14 00:12:00 :: administrator -> :: 2000
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsface recognition
face discrimination
Fourier descriptors
feature selection
horizontal edge detection filter
1D signal extraction
image classification
statistical classifiers
performance assessment
transform based methods
face detection
AbstractThis work presents a new method to discriminate face from non-face images using Fourier descriptors. The first step of our approach consists in applying a horizontal edge detection filter in the input image, followed by the extraction of a 1D signal from the computed edge map. Then we calculate the Fourier descriptors from this signal and classify the image using statistical classifiers. In order to improve our results, we applied a feature selection algorithm. Preliminary performance assessment results have shown that this approach is superior than traditional transform based methods. Besides, these results showed that our method might be used to develop a fast face detection system.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2000 > Improved face/spl times/non-face...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Improved face/spl times/non-face...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
data URLhttp://urlib.net/ibi/6qtX3pFwXQZeBBx/w4mtv
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZeBBx/w4mtv
Target File28-35.pdf
User Groupadministrator
Visibilityshown
5. Allied materials
Next Higher Units8JMKD3MGPEW34M/46PN6AP
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/04.27.03.08 2
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
NotesThe conference was held in Gramado, RS, Brazil, from October 17 to 20.
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