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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3M9GPQ8
Repositorysid.inpe.br/sibgrapi/2016/08.15.21.28
Last Update2016:08.15.21.28.25 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2016/08.15.21.28.25
Metadata Last Update2022:05.18.22.21.07 (UTC) administrator
Citation KeyJordãoSchw:2016:GoFaBe
TitleThe Good, The Fast and The Better Pedestrian Detector
FormatOn-line
Year2016
Access Date2024, Apr. 28
Number of Files1
Size534 KiB
2. Context
Author1 Jordão, Artur
2 Schwartz, William Robson
Affiliation1 DCC-UFMG
2 DCC-UFMG
EditorAliaga, Daniel G.
Davis, Larry S.
Farias, Ricardo C.
Fernandes, Leandro A. F.
Gibson, Stuart J.
Giraldi, Gilson A.
Gois, João Paulo
Maciel, Anderson
Menotti, David
Miranda, Paulo A. V.
Musse, Soraia
Namikawa, Laercio
Pamplona, Mauricio
Papa, João Paulo
Santos, Jefersson dos
Schwartz, William Robson
Thomaz, Carlos E.
e-Mail Addressarturjlcorreia@gmail.com
Conference NameConference on Graphics, Patterns and Images, 29 (SIBGRAPI)
Conference LocationSão José dos Campos, SP, Brazil
Date4-7 Oct. 2016
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeMaster's or Doctoral Work
History (UTC)2016-08-15 21:28:25 :: arturjlcorreia@gmail.com -> administrator ::
2022-05-18 22:21:07 :: administrator -> :: 2016
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsOblique Decision Tree
Partial Least Squares
Filtering Approaches
High-Level Information
Fusion of Detectors
AbstractPedestrian detection is a well-known problem in Computer Vision, mostly because of its direct applications in surveillance, transit safety and robotics. In the past decade, several efforts have been performed to improve the detection in terms of accuracy, velocity and enhancement of features. In this work, we proposed and analyzed techniques focusing on these points. Firstly, we propose an accurate oblique random forest associated with Partial Least Squares (PLS). The method consists on utilize the PLS to find a decision surface at each node in a decision tree. Secondly, we evaluate filtering approaches to reduce the search space and keep only potential regions of interest to be presented to detectors, speeding up the detection process. Finally, we propose a novel approach to extract powerful features regarding the scene. The method combines results of distinct pedestrian detectors by reinforcing the human hypothesis whereas suppressing a significant number of false positives.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2016 > The Good, The...
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source Directory Contentthere are no files
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3M9GPQ8
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3M9GPQ8
Languageen
Target FileMain.pdf
User Grouparturjlcorreia@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3M2D4LP
Citing Item Listsid.inpe.br/sibgrapi/2016/07.02.23.50 6
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi 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 versiontype volume


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