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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/45E5JRH
Repositorysid.inpe.br/sibgrapi/2021/09.13.22.19
Last Update2021:10.02.17.36.22 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2021/09.13.22.19.25
Metadata Last Update2022:09.10.00.16.17 (UTC) administrator
Citation KeyHuaytaClúaGuér:2021:NoHuHy
TitleA Novel Human-Machine Hybrid Framework for Person Re-Identification from Full Frame Videos
FormatOn-line
Year2021
Access Date2022, Dec. 07
Number of Files1
Size1494 KiB
2. Context
Author1 Huayta, Felix Oliver Sumari
2 Clúa, Esteban Walter Gonzales
3 Guérin, Joris
Affiliation1 Universidade Federal Fluminense - Instituto de Computação
2 Universidade Federal Fluminense - Instituto de Computação
3 Université de Toulouse
EditorPaiva, Afonso
Menotti, David
Baranoski, Gladimir V. G.
Proença, Hugo Pedro
Junior, Antonio Lopes Apolinario
Papa, João Paulo
Pagliosa, Paulo
dos Santos, Thiago Oliveira
e Sá, Asla Medeiros
da Silveira, Thiago Lopes Trugillo
Brazil, Emilio Vital
Ponti, Moacir A.
Fernandes, Leandro A. F.
Avila, Sandra
e-Mail Addressfsumari@id.uff.br
Conference NameConference on Graphics, Patterns and Images, 34 (SIBGRAPI)
Conference LocationGramado, RS, Brazil (virtual)
Date18-22 Oct. 2021
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeMaster's or Doctoral Work
History (UTC)2021-10-07 02:42:33 :: fsumari@id.uff.br -> administrator :: 2021
2022-09-10 00:16:17 :: administrator -> :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsSecurity Application
Person Re-Identification
Pedestrian Detection
AbstractWith the major adoption of automation for cities security, person re-identification (Re-ID) has been extensively studied. In this dissertation, we argue that the current way of studying person re-identification, i.e. by trying to re-identify a person within already detected and pre-cropped images of people, is not sufficient to implement practical security applications, where the inputs to the system are the full frames of the video streams. To support this claim, we introduce the Full Frame Person Re-ID setting and define specific metrics to evaluate FF-PRID implementations. To improve robustness, we also formalize the hybrid human-machine collaboration framework, which is inherent to any Re-ID security applications. To demonstrate the importance of considering the FF-PRID setting, we build an experiment showing that combining a good people detection network with a good Re-ID model does not necessarily produce good results for the final application. This underlines a failure of the current formulation in assessing the quality of a Re-ID model and justifies the use of different metrics. We hope that this work will motivate the research community to consider the full problem in order to develop algorithms that are better suited to real-world scenarios.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2021 > A Novel Human-Machine...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/45E5JRH
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/45E5JRH
Languageen
Target FilePAPER_SIBGRAPI_2021_CAMERA_READY.pdf
User Groupfsumari@id.uff.br
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/45PQ3RS
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage 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 secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume


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