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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/387M46P
Repositorysid.inpe.br/sibgrapi/2010/09.06.14.05
Last Update2010:09.06.14.05.16 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2010/09.06.14.05.16
Metadata Last Update2022:06.14.00.06.58 (UTC) administrator
DOI10.1109/SIBGRAPI.2010.33
Citation KeyNomaJr:2010:SpReEf
TitleSparse Representations for Efficient Shape Matching
FormatPrinted, On-line.
Year2010
Access Date2024, May 03
Number of Files1
Size521 KiB
2. Context
Author1 Noma, Alexandre
2 Jr, Roberto Marcondes Cesar
Affiliation1 Instituto de Matemática e Estatística - USP
2 Instituto de Matemática e Estatística - USP
EditorBellon, Olga
Esperança, Claudio
e-Mail Addressalex.noma@gmail.com
Conference NameConference on Graphics, Patterns and Images, 23 (SIBGRAPI)
Conference LocationGramado, RS, Brazil
Date30 Aug.-3 Sep. 2010
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2010-10-01 04:19:39 :: alex.noma@gmail.com -> administrator :: 2010
2022-06-14 00:06:58 :: administrator -> :: 2010
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordspoint pattern matching
graph matching
quadratic assignment
Markov random fields
efficient belief propagation
sparse shape representations
shape metric
3D object recognition
handwritten digits
AbstractGraph matching is a fundamental problem with many applications in computer vision. Patterns are represented by graphs and pattern recognition corresponds to finding a correspondence between vertices from different graphs. In many cases, the problem can be formulated as a quadratic assignment problem, where the cost function consists of two components: a linear term representing the vertex compatibility and a quadratic term encoding the edge compatibility. The quadratic assignment problem is NP-hard and the present paper extends the approximation technique based on graph matching and efficient belief propagation described in previous work by using sparse representations for efficient shape matching. Successful results of recognition of 3D objects and handwritten digits are illustrated, using COIL and MNIST datasets, respectively. .
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2010 > Sparse Representations for...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Sparse Representations for...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/387M46P
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/387M46P
Languageen
Target Filepaper2.pdf
User Groupalex.noma@gmail.com
Visibilityshown
5. Allied materials
Next Higher Units8JMKD3MGPEW34M/46SJT6B
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.14.20.21 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 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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