About: Face Templates Creration for Surveillance Face Recognition System     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
Description
  • This paper addresses the problem of face templates creation for facial recognition system. The application of a face recognition system in real-world conditions requires compact and representative face templates in order to maintain low error rate and low classification time. Contemporary face template creation methods are not suitable for face recognition systems with large number of users as they produce many templates per person. These templates are often redundant and their high number requires long classification time. The paper presents four approaches to face templates creation that produce one to three face templates per person. The influence of different face template creation approaches was assessed on PubFig and IFaViD database. The achieved results show that appropriate face template creation methods have a significant influence on face recognition system performance.
  • This paper addresses the problem of face templates creation for facial recognition system. The application of a face recognition system in real-world conditions requires compact and representative face templates in order to maintain low error rate and low classification time. Contemporary face template creation methods are not suitable for face recognition systems with large number of users as they produce many templates per person. These templates are often redundant and their high number requires long classification time. The paper presents four approaches to face templates creation that produce one to three face templates per person. The influence of different face template creation approaches was assessed on PubFig and IFaViD database. The achieved results show that appropriate face template creation methods have a significant influence on face recognition system performance. (en)
  • This paper addresses the problem of face templates creation for facial recognition system. The application of a face recognition system in real-world conditions requires compact and representative face templates in order to maintain low error rate and low classification time. Contemporary face template creation methods are not suitable for face recognition systems with large number of users as they produce many templates per person. These templates are often redundant and their high number requires long classification time. The paper presents four approaches to face templates creation that produce one to three face templates per person. The influence of different face template creation approaches was assessed on PubFig and IFaViD database. The achieved results show that appropriate face template creation methods have a significant influence on face recognition system performance. (cs)
Title
  • Face Templates Creration for Surveillance Face Recognition System
  • Face Templates Creration for Surveillance Face Recognition System (en)
  • Face Templates Creration for Surveillance Face Recognition System (cs)
skos:prefLabel
  • Face Templates Creration for Surveillance Face Recognition System
  • Face Templates Creration for Surveillance Face Recognition System (en)
  • Face Templates Creration for Surveillance Face Recognition System (cs)
skos:notation
  • RIV/00216305:26220/14:PU108846!RIV15-MSM-26220___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED2.1.00/03.0072)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 16304
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/14:PU108846
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Face templates, template database creation, face recognition system application, real-world conditons (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [E409E71A6DAF]
http://linked.open...v/mistoKonaniAkce
  • Angers
http://linked.open...i/riv/mistoVydani
  • Neuveden
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Přinosil, Jiří
  • Malach, Tobiáš
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Neuveden
https://schema.org/isbn
  • 978-989-758-018-5
http://localhost/t...ganizacniJednotka
  • 26220
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software