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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPBW34M/3C9BFTH
Repositorysid.inpe.br/sibgrapi/2012/07.12.00.16
Last Update2012:07.12.00.16.47 rafaelufrn@gmail.com
Metadatasid.inpe.br/sibgrapi/2012/07.12.00.16.47
Metadata Last Update2020:02.19.02.18.27 administrator
Citation KeyGomesArocCarvGonš:2012:ReTiIn
TitleReal time Interactive Image Segmentation Using User Indicated Real-world Seeds
FormatDVD, On-line.
Year2012
Access Date2021, Jan. 24
Number of Files1
Size1701 KiB
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Author1 Gomes, Rafael Beserra
2 Aroca, Rafael Vidal
3 Carvalho, Bruno Motta de
4 Gonšalves, Luiz Marcos Garcia
Affiliation1 Universidade Federal do Rio Grande do Norte
2 Universidade Federal do Rio Grande do Norte
3 Universidade Federal do Rio Grande do Norte
4 Universidade Federal do Rio Grande do Norte
EditorFreitas, Carla Maria Dal Sasso
Sarkar, Sudeep
Scopigno, Roberto
Silva, Luciano
e-Mail Addressrafaelufrn@gmail.com
Conference NameConference on Graphics, Patterns and Images, 25 (SIBGRAPI)
Conference LocationOuro Preto
DateAug. 22-25, 2012
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2012-09-20 16:45:34 :: rafaelufrn@gmail.com -> administrator :: 2012
2020-02-19 02:18:27 :: administrator -> :: 2012
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Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Keywordsinteractive computer vision, real-time, seed selection, fuzzy image segmentation.
AbstractWe propose a novel and fast interactive segmentation methodology for computer vision applications. Basically, the proposed system performs the tracking of seeds so that multiple seeds can be acquired over time, substantially improving the segmentation results. Moreover, instead of image coordinates, the user indicates points in the real-world that become seeds in the image. These seeds can be indicated, for example using a laser pointer or a smart-phone. The seeds can then be tracked and used by a segmentation algorithm. Experiments using the Lucas-Kanade Optical Flow and the Fast Multi-Object Fuzzy Segmentation (Fast-MOFS) algorithm demonstrate that the proposed technique successfully segments images in real-time and improves the user ability to directly segment an object in the real world. The proposed system has a high performance, allowing it to be used with high frame rates in devices with low processing capability and/or with restricted power requirements.
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data URLhttp://urlib.net/rep/8JMKD3MGPBW34M/3C9BFTH
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3C9BFTH
Languageen
Target FilePID2444915.pdf
User Grouprafaelufrn@gmail.com
Visibilityshown
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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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