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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZG2LgkFdY/LzdxM
Repositorysid.inpe.br/sibgrapi@80/2006/06.26.11.48
Last Update2006:07.10.17.21.57 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi@80/2006/06.26.11.48.25
Metadata Last Update2022:06.14.00.13.08 (UTC) administrator
DOI10.1109/SIBGRAPI.2006.23
Citation KeyRibeiroGonz:2006:CoAn
TitleHand Image Segmentation in Video Sequence by GMM: a comparative analysis
FormatOn-line
Year2006
Access Date2024, Apr. 30
Number of Files1
Size1015 KiB
2. Context
Author1 Ribeiro, Hebert Luchetti
2 Gonzaga, Adilson
Affiliation1 School of Engineering at Sao Carlos
2 School of Engineering at Sao Carlos
EditorOliveira Neto, Manuel Menezes de
Carceroni, Rodrigo Lima
e-Mail Addressagonzaga@sc.usp.br
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 19 (SIBGRAPI)
Conference LocationManaus, AM, Brazil
Date8-11 Oct. 2006
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2006-07-10 17:21:58 :: adilson -> banon ::
2006-08-30 21:58:08 :: banon -> adilson ::
2008-07-17 14:11:02 :: adilson -> administrator ::
2009-08-13 20:38:00 :: administrator -> banon ::
2010-08-28 20:02:22 :: banon -> administrator ::
2022-06-14 00:13:08 :: administrator -> :: 2006
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsVideo Image Segmentation
Gaussian Mixture Model
AbstractThis paper describes different approaches of realtimeGMM (Gaussian Mixture Method) backgroundsubtraction algorithm using video sequences for handimage segmentation. In each captured image, thesegmentation takes place where pixels belonging to thehands are separated from the background based onbackground extraction and skin-color segmentation. Atime-adaptive mixture of Gaussians is used to modelthe distribution of each pixel color value. For an inputimage, every new pixel value is checked, deciding if itmatches with one of the existing Gaussians based onthe distance from the mean in terms of the standarddeviation. The best matching distribution parametersare updated and its weight is increased. It is assumedthat the values of the background pixels have lowvariance and large weight. These matched pixels,considered as foreground, are compared based on skincolor thresholds. The hands position and otherattributes are tracked by frame. That enables us todistinguish the hand movement from the backgroundand other objects in movement, as well as to extractthe information from the movement for dynamic handgesture recognition.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2006 > Hand Image Segmentation...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Hand Image Segmentation...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/LzdxM
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZG2LgkFdY/LzdxM
Languageen
Target FileRibeiro-HandImageSegmentationInVideoSequenceByGMM.pdf
User Groupadilson
administrator
Visibilityshown
5. Allied materials
Next Higher Units8JMKD3MGPEW34M/46RFT7E
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.08.00.20 5
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage edition electronicmailaddress group isbn issn label lineage mark mirrorrepository 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


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