Identity statement area
Reference TypeConference Paper (Conference Proceedings)
Last Update2013:
Metadata Last Update2020: administrator
Citation KeyRauberFalcSpinReze:2013:InSeIm
TitleInteractive segmentation by image foresting transform on superpixel graphs
Access Date2021, Jan. 27
Number of Files1
Size3983 KiB
Context area
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
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 :: -> administrator ::
2020-02-19 03:09:22 :: administrator -> :: 2013
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
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.
source Directory Contentthere are no files
agreement Directory Content
agreement.html 04/07/2013 18:42 0.7 KiB 
Conditions of access and use area
data URL
zipped data URL
Target Filearticle_checked.pdf
Allied materials area
Notes area
Empty Fieldsaccessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition nexthigherunit 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 versiontype volume