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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZG2LgkFdY/V8gFt
Repositorysid.inpe.br/sibgrapi@80/2008/08.11.17.14
Last Update2008:08.11.17.14.53 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi@80/2008/08.11.17.14.56
Metadata Last Update2022:05.18.22.21.18 (UTC) administrator
DOI10.1109/SIBGRAPI.2008.32
Citation KeyPaixãoGracJrJr:2008:BaApGr
TitleA Backmapping Approach for Graph-based Object Tracking
FormatPrinted, On-line.
Year2008
Access Date2022, May 21
Number of Files1
Size9750 KiB
2. Context
Author1 Paixão, Thiago Meireles
2 Graciano, Ana Beatriz V.
3 Jr, Roberto M. Cesar
4 Jr, Roberto Hirata
Affiliation1 Instituto de Matemática e Estatística - USP
2 Instituto de Matemática e Estatística - USP
3 Instituto de Matemática e Estatística - USP
4 Instituto de Matemática e Estatística - USP
EditorJung, Cláudio Rosito
Walter, Marcelo
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 21 (SIBGRAPI)
Conference LocationCampo Grande, MS, Brazil
Date12-15 Oct. 2008
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2008-08-11 17:14:56 :: hirata@ime.usp.br -> administrator ::
2009-08-13 20:39:04 :: administrator -> hirata@ime.usp.br ::
2010-08-28 20:03:24 :: hirata@ime.usp.br -> administrator ::
2022-05-18 22:21:18 :: administrator -> :: 2008
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsDigital Image Processing
Graph-based Segmentation
Object Tracking
AbstractModel-based methods play a central role to solve different problems in computer vision. A particular important class of such methods rely on graph models where an object is decomposed into a number of parts, each one being represented by a graph vertex. A graph model-based tracking algorithm has been recently introduced in which a model is generated for a given frame (reference frame) and used to track a target object in the subsequent ones. Because the view of an object changes along the video sequence, the solution updated the model using affine transformations. This paper proposes a different approach and improves the previous one in several ways. Firstly, instead of updating the model, each analyzed frame is backmapped to the model space, thus providing more robustness to the method because model parameters do not have to be modified. A different method for model generation based on user traces has also been implemented and used. This model generation approach is much simpler and user-friendly. Finally, a graph-matching algorithm that has been recently proposed is used for object tracking. This new algorithm is more efficient and leads to better matching results. Experimental results using synthetic and real sequences from the CAVIAR project are shown and discussed. .
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/V8gFt
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZG2LgkFdY/V8gFt
Languageen
Target Filehirata-Backmapping.pdf
User Grouphirata@ime.usp.br
administrator
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/46SG4TH
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsaccessionnumber archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage e-mailaddress edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


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