Journal article Open Access

Video-Based Person Re-Identification: Methods, Datasets, and Deep Learning

Manisha Talware; Sanjay Koli


DCAT Export

<?xml version='1.0' encoding='utf-8'?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:adms="http://www.w3.org/ns/adms#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dct="http://purl.org/dc/terms/" xmlns:dctype="http://purl.org/dc/dcmitype/" xmlns:dcat="http://www.w3.org/ns/dcat#" xmlns:duv="http://www.w3.org/ns/duv#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:frapo="http://purl.org/cerif/frapo/" xmlns:geo="http://www.w3.org/2003/01/geo/wgs84_pos#" xmlns:gsp="http://www.opengis.net/ont/geosparql#" xmlns:locn="http://www.w3.org/ns/locn#" xmlns:org="http://www.w3.org/ns/org#" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:prov="http://www.w3.org/ns/prov#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:schema="http://schema.org/" xmlns:skos="http://www.w3.org/2004/02/skos/core#" xmlns:vcard="http://www.w3.org/2006/vcard/ns#" xmlns:wdrs="http://www.w3.org/2007/05/powder-s#">
  <rdf:Description rdf:about="https://zenodo.org/record/5595720">
    <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#anyURI">https://zenodo.org/record/5595720</dct:identifier>
    <foaf:page rdf:resource="https://zenodo.org/record/5595720"/>
    <dct:creator>
      <rdf:Description>
        <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/>
        <foaf:name>Manisha Talware</foaf:name>
        <org:memberOf>
          <foaf:Organization>
            <foaf:name>Research Scholar at G.H. Raisoni College of Engineering and Management, Pune, India</foaf:name>
          </foaf:Organization>
        </org:memberOf>
      </rdf:Description>
    </dct:creator>
    <dct:creator>
      <rdf:Description>
        <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/>
        <foaf:name>Sanjay Koli</foaf:name>
        <org:memberOf>
          <foaf:Organization>
            <foaf:name>Professor, D. Y. Patil Inst. of Info. Technology and Research Supervisor at G.H. Raisoni College of Engineering and Management, Pune, Indi</foaf:name>
          </foaf:Organization>
        </org:memberOf>
      </rdf:Description>
    </dct:creator>
    <dct:title>Video-Based Person Re-Identification: Methods, Datasets, and Deep Learning</dct:title>
    <dct:publisher>
      <foaf:Agent>
        <foaf:name>Zenodo</foaf:name>
      </foaf:Agent>
    </dct:publisher>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2020</dct:issued>
    <dcat:keyword>Person Re-Identification, Camera Network, Video Analytics, Deep Learning, pedestrian detection.</dcat:keyword>
    <dct:subject>
      <skos:Concept>
        <skos:prefLabel>2249-8958</skos:prefLabel>
        <skos:inScheme>
          <skos:ConceptScheme>
            <dct:title>issn</dct:title>
          </skos:ConceptScheme>
        </skos:inScheme>
      </skos:Concept>
    </dct:subject>
    <dct:subject>
      <skos:Concept>
        <skos:prefLabel>C6524029320 /2020©BEIESP</skos:prefLabel>
        <skos:inScheme>
          <skos:ConceptScheme>
            <dct:title>handle</dct:title>
          </skos:ConceptScheme>
        </skos:inScheme>
      </skos:Concept>
    </dct:subject>
    <schema:sponsor>
      <rdf:Description>
        <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/>
        <foaf:name>Blue Eyes Intelligence Engineering &amp; Sciences Publication (BEIESP)</foaf:name>
        <org:memberOf>
          <foaf:Organization>
            <foaf:name>Publisher</foaf:name>
          </foaf:Organization>
        </org:memberOf>
      </rdf:Description>
    </schema:sponsor>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2020-02-29</dct:issued>
    <dct:language rdf:resource="http://publications.europa.eu/resource/authority/language/ENG"/>
    <owl:sameAs rdf:resource="https://zenodo.org/record/5595720"/>
    <adms:identifier>
      <adms:Identifier>
        <skos:notation rdf:datatype="http://www.w3.org/2001/XMLSchema#anyURI">https://zenodo.org/record/5595720</skos:notation>
        <adms:schemeAgency>url</adms:schemeAgency>
      </adms:Identifier>
    </adms:identifier>
    <dct:relation rdf:resource="http://issn.org/resource/ISSN/2249-8958"/>
    <owl:sameAs rdf:resource="https://doi.org/10.35940/ijeat.C6524.029320"/>
    <dct:description>&lt;p&gt;Video Analytics applications like security and surveillance face a critical problem of person re-identification abbreviated as re-ID. The last decade witnessed the emergence of large-scale datasets and deep learning methods to use these huge data volumes. Most current re-ID methods are classified into either image-based or video-based re-ID. Matching persons across multiple camera views have attracted lots of recent research attention. Feature representation and metric learning are major issues for person re-identification. The focus of re-ID work is now shifting towards developing end-to-end re-Id and tracking systems for practical use with dynamic datasets. Most previous works contributed to the significant progress of person re-identification on still images using image retrieval models. This survey considers the more informative and challenging video-based person re-ID problem, pedestrian re-ID in particular. Publicly available datasets and codes are listed as a part of this work. Current trends which include open re-identification systems, use of discriminative features and deep learning is marching towards new applications in security and surveillance, typically for tracking.&lt;/p&gt;</dct:description>
    <dct:accessRights rdf:resource="http://publications.europa.eu/resource/authority/access-right/PUBLIC"/>
    <dct:accessRights>
      <dct:RightsStatement rdf:about="info:eu-repo/semantics/openAccess">
        <rdfs:label>Open Access</rdfs:label>
      </dct:RightsStatement>
    </dct:accessRights>
    <dct:license rdf:resource="https://creativecommons.org/licenses/by/4.0/legalcode"/>
    <dcat:distribution>
      <dcat:Distribution>
        <dcat:accessURL rdf:resource="https://doi.org/10.35940/ijeat.C6524.029320"/>
        <dcat:byteSize>790903</dcat:byteSize>
        <dcat:downloadURL rdf:resource="https://zenodo.org/record/5595720/files/C6524029320.pdf"/>
        <dcat:mediaType>application/pdf</dcat:mediaType>
      </dcat:Distribution>
    </dcat:distribution>
  </rdf:Description>
</rdf:RDF>
36
15
views
downloads
Views 36
Downloads 15
Data volume 11.9 MB
Unique views 36
Unique downloads 15

Share

Cite as