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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZG2LgkFdY/QRrno
Repositorysid.inpe.br/sibgrapi@80/2007/07.24.18.40
Last Update2007:07.24.18.40.55 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi@80/2007/07.24.18.40.57
Metadata Last Update2022:06.14.00.13.34 (UTC) administrator
DOI10.1109/SIBGRAPI.2007.43
Citation KeyGracianoCesaBloc:2007:GrObTr
TitleGraph-based Object Tracking Using Structural Pattern Recognition
FormatPrinted, On-line.
Year2007
Access Date2024, Oct. 15
Number of Files1
Size2524 KiB
2. Context
Author1 Graciano, Ana Beatriz Vicentim
2 Cesar-Jr, Roberto M.
3 Bloch, Isabelle
Affiliation1 Institute of Mathematics and Statistics - University of São Paulo
2 Institute of Mathematics and Statistics - University of São Paulo
3 Dept. TSI - ENST - Paris
EditorFalcão, Alexandre Xavier
Lopes, Hélio Côrtes Vieira
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI)
Conference LocationBelo Horizonte, MG, Brazil
Date7-10 Oct. 2007
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2007-07-31 18:46:15 :: anabvg@gmail.com -> administrator ::
2007-08-02 21:17:35 :: administrator -> anabvg@gmail.com ::
2008-07-17 14:09:43 :: anabvg@gmail.com -> administrator ::
2009-08-13 20:38:26 :: administrator -> banon ::
2010-08-28 20:02:28 :: banon -> administrator ::
2022-06-14 00:13:34 :: administrator -> :: 2007
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsobject tracking
recognition
part-based
graph
video
AbstractThis paper proposes a model-based methodology for recognizing and tracking objects in digital image sequences. Objects are represented by attributed relational graphs (or ARGs), which carry both local and relational information about them. The recognition is performed by inexact graph matching, which consists in finding an approximate homomorphism between ARGs derived from an input video and a model image. Searching for a suitable homomorphism is achieved through a tree-search optimization algorithm and the minimization of a pre-defined cost function. Motion smoothness between successive frames is exploited to achieve the recognition over the whole sequence, with improved spatio-temporal coherence.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2007 > Graph-based Object Tracking...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Graph-based Object Tracking...
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/6qtX3pFwXQZG2LgkFdY/QRrno
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZG2LgkFdY/QRrno
Languageen
Target Filegraciano-GraphBasedTracking.pdf
User Groupanabvg@gmail.com
administrator
Visibilityshown
5. Allied materials
Next Higher Units8JMKD3MGPEW34M/46SF8Q5
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.14.00.14 37
sid.inpe.br/sibgrapi/2022/06.10.21.49 4
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage e-mailaddress 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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