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Description
  • The paper focuses on Automatic Face Recognition (AFR) under real-world conditions. Two previously proposed AFR methods are evaluated on real-world data. There is a comparison of the results on a standard dataset and a newly created real-world dataset. Further, the process of automatic creation of the ČTK dataset is described. Automatic Face Recognition, Czech News Agency, Confidence Measures, Gabor Wavelets, Scale Invariant Feature TransformThen a series of experiments on this dataset is presented. It is shown that the recognition rate is influenced by the number of training images for each person. It is also demonstrated, that the recognition rate decreases significantly with larger database. Next, the use of a confidence measure technique as a solution to identify and to filter-out the incorrectly recognized faces is proposed. It is shown that the confidence measure is very beneficial for AFR under real-world conditions.
  • The paper focuses on Automatic Face Recognition (AFR) under real-world conditions. Two previously proposed AFR methods are evaluated on real-world data. There is a comparison of the results on a standard dataset and a newly created real-world dataset. Further, the process of automatic creation of the ČTK dataset is described. Automatic Face Recognition, Czech News Agency, Confidence Measures, Gabor Wavelets, Scale Invariant Feature TransformThen a series of experiments on this dataset is presented. It is shown that the recognition rate is influenced by the number of training images for each person. It is also demonstrated, that the recognition rate decreases significantly with larger database. Next, the use of a confidence measure technique as a solution to identify and to filter-out the incorrectly recognized faces is proposed. It is shown that the confidence measure is very beneficial for AFR under real-world conditions. (en)
Title
  • Automatic Face Corpus Creation
  • Automatic Face Corpus Creation (en)
skos:prefLabel
  • Automatic Face Corpus Creation
  • Automatic Face Corpus Creation (en)
skos:notation
  • RIV/49777513:23520/13:43918331!RIV14-MSM-23520___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED1.1.00/02.0090), S
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
  • 62608
http://linked.open...ai/riv/idVysledku
  • RIV/49777513:23520/13:43918331
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Scale Invariant Feature Transform; Gabor Wavelets; Confidence Measures; Czech News Agency; Automatic Face Recognition (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [B594EC71C072]
http://linked.open...v/mistoKonaniAkce
  • Barcelona
http://linked.open...i/riv/mistoVydani
  • Setúbal
http://linked.open...i/riv/nazevZdroje
  • ICAART 2013
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
  • Král, Pavel
  • Lenc, Ladislav
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • SciTePress
https://schema.org/isbn
  • 978-989-8565-38-9
http://localhost/t...ganizacniJednotka
  • 23520
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