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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3EDGFSB
Repositorysid.inpe.br/sibgrapi/2013/07.04.21.42
Last Update2013:07.04.21.42.45 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2013/07.04.21.42.45
Metadata Last Update2022:05.18.22.20.51 (UTC) administrator
DOI10.1109/SIBGRAPI.2013.27
Citation KeyRauberFalcSpinReze:2013:InSeIm
TitleInteractive segmentation by image foresting transform on superpixel graphs
FormatOn-line.
Year2013
Access Date2022, May 21
Number of Files1
Size3983 KiB
2. Context
Author1 Rauber, Paulo Eduardo
2 Falc„o, Alexandre Xavier
3 Spina, Thiago Vallin
4 Rezende, Pedro Jussieu de
Affiliation1 University of Campinas (UNICAMP)
2 University of Campinas (UNICAMP)
3 University of Campinas (UNICAMP)
4 University of Campinas (UNICAMP)
EditorBoyer, Kim
Hirata, Nina
Nedel, Luciana
Silva, Claudio
e-Mail Addresspauloeduardorauber@gmail.com
Conference NameConference on Graphics, Patterns and Images, 26 (SIBGRAPI)
Conference LocationArequipa, Peru
Date5-8 Aug. 2013
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2013-07-04 21:42:45 :: pauloeduardorauber@gmail.com -> administrator ::
2022-05-18 22:20:51 :: administrator -> :: 2013
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsgraph-based image segmentation
image foresting transform
robot users
interactive segmentation
AbstractThere are many scenarios in which user interaction is essential for effective image segmentation. In this paper, we present a new interactive segmentation method based on the Image Foresting Transform (IFT). The method oversegments the input image, creates a graph based on these segments (superpixels), receives markers (labels) drawn by the user on some superpixels and organizes a competition to label every pixel in the image. Our method has several interesting properties: it is effective, efficient, capable of segmenting multiple objects in almost linear time on the number of superpixels, readily extendable through previously published techniques, and benefits from domain-specific feature extraction. We also present a comparison with another technique based on the IFT, which can be seen as its pixel-based counterpart. Another contribution of this paper is the description of automatic (robot) users. Given a ground truth image, these robots simulate interactive segmentation by trained and untrained users, reducing the costs and biases involved in comparing segmentation techniques.
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3EDGFSB
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3EDGFSB
Languageen
Target Filearticle_checked.pdf
User Grouppauloeduardorauber@gmail.com
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/46SLB4P
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 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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