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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPBW34M/3EDGFSB
Repositorysid.inpe.br/sibgrapi/2013/07.04.21.42
Last Update2013:07.04.21.42.45 pauloeduardorauber@gmail.com
Metadatasid.inpe.br/sibgrapi/2013/07.04.21.42.45
Metadata Last Update2020:02.19.03.09.22 administrator
Citation KeyRauberFalcSpinReze:2013:InSeIm
TitleInteractive segmentation by image foresting transform on superpixel graphs
FormatOn-line.
Year2013
Access Date2021, Jan. 27
Number of Files1
Size3983 KiB
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Author1 Rauber, Paulo Eduardo
2 Falcão, 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
DateAug. 5-8, 2013
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2013-07-04 21:42:45 :: pauloeduardorauber@gmail.com -> administrator ::
2020-02-19 03:09:22 :: administrator -> :: 2013
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Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
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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data URLhttp://urlib.net/rep/8JMKD3MGPBW34M/3EDGFSB
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3EDGFSB
Languageen
Target Filearticle_checked.pdf
User Grouppauloeduardorauber@gmail.com
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Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
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