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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3PFRN5P
Repositorysid.inpe.br/sibgrapi/2017/08.21.23.41
Last Update2017:08.21.23.41.10 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2017/08.21.23.41.10
Metadata Last Update2022:06.14.00.09.01 (UTC) administrator
DOI10.1109/SIBGRAPI.2017.51
Citation KeySennaDrumBast:2017:ReEnTr
TitleReal-time ensemble-based tracker with Kalman filter
FormatOn-line
Year2017
Access Date2024, May 01
Number of Files1
Size207 KiB
2. Context
Author1 Senna, Pedro
2 Drummond, Isabela Neves
3 Bastos, Guilherme Sousa
Affiliation1 Universidade Federal de Itajubá
2 Universidade Federal de Itajubá
3 Universidade Federal de Itajubá
EditorTorchelsen, Rafael Piccin
Nascimento, Erickson Rangel do
Panozzo, Daniele
Liu, Zicheng
Farias, Mylčne
Viera, Thales
Sacht, Leonardo
Ferreira, Nivan
Comba, Joăo Luiz Dihl
Hirata, Nina
Schiavon Porto, Marcelo
Vital, Creto
Pagot, Christian Azambuja
Petronetto, Fabiano
Clua, Esteban
Cardeal, Flávio
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ, Brazil
Date17-20 Oct. 2017
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2017-08-21 23:41:10 :: pedrosennapsc#gmail.com -> administrator ::
2022-06-14 00:09:01 :: administrator -> :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsUniversidade Federal de Itajubá
AbstractThis work presents an ensemble-based visual object tracker called KFebT. This method can fuse using a Kalman Filter the result of several out-of-the box trackers or specialist methods that solve parts of the problem, like methods that only estimate the target scale variation. Our purpose in joining multiple trackers is to take advantage of the different strengths and weaknesses of each approach. The proposed fusion method is simple and needs no training; it just needs the tracker output result and a confidence measure for the result of each tracker. We performed tests on the Visual Object Tracking Challenge (VOT) 2015 dataset and evaluated our tracker in terms of expected overlap, accuracy and robustness. We test our proposed method on combination of two and three tracking algorithms and the results demonstrate clear improvements over the trackers used in its composition.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2017 > Real-time ensemble-based tracker...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Real-time ensemble-based tracker...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3PFRN5P
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PFRN5P
Languageen
Target FilePID4960379.pdf
User Grouppedrosennapsc#gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3PKCC58
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2017/09.12.13.04 5
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination e-mailaddress edition electronicmailaddress group isbn issn label lineage mark 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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