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Description
  • In this paper we focus on appearance features describing the manual component of Sign Language particularly the Local Binary Patterns. We compare the performance of these features with geometric moments describing the trajectory and shape of hands. Since the non-manual component is also very important for sign recognition we localize facial landmarks via Active Shape Model combined with Landmark detector that increases the robustness of model fitting. We test the recognition performance of individual features and their combinations on a database consisting of 11 signers and 23 signs with several repetitions. Local Binary Patterns outperform the geometric moments. When the features are combined we achieve a recognition rate up to 99.75% for signer dependent tests and 57.54% for signer independent tests.
  • In this paper we focus on appearance features describing the manual component of Sign Language particularly the Local Binary Patterns. We compare the performance of these features with geometric moments describing the trajectory and shape of hands. Since the non-manual component is also very important for sign recognition we localize facial landmarks via Active Shape Model combined with Landmark detector that increases the robustness of model fitting. We test the recognition performance of individual features and their combinations on a database consisting of 11 signers and 23 signs with several repetitions. Local Binary Patterns outperform the geometric moments. When the features are combined we achieve a recognition rate up to 99.75% for signer dependent tests and 57.54% for signer independent tests. (en)
Title
  • Local Binary Pattern Based Features for Sign Language Recognition
  • Local Binary Pattern Based Features for Sign Language Recognition (en)
skos:prefLabel
  • Local Binary Pattern Based Features for Sign Language Recognition
  • Local Binary Pattern Based Features for Sign Language Recognition (en)
skos:notation
  • RIV/49777513:23520/11:43898225!RIV12-MSM-23520___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ME08106), S
http://linked.open...iv/cisloPeriodika
  • 3
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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http://linked.open...dnocenehoVysledku
  • 209786
http://linked.open...ai/riv/idVysledku
  • RIV/49777513:23520/11:43898225
http://linked.open...riv/jazykVysledku
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  • Local Binary Pattern, Sign Language, Sign Language Recognition (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • RU - Ruská federace
http://linked.open...ontrolniKodProRIV
  • [B2023E5FD1B7]
http://linked.open...i/riv/nazevZdroje
  • Pattern Recognition and Image Analysis
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
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http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 21
http://linked.open...iv/tvurceVysledku
  • Hrúz, Marek
  • Železný, Miloš
  • Trojanová, Jana
issn
  • 1054-6618
number of pages
http://bibframe.org/vocab/doi
  • 10.1134/S1054661811020416
http://localhost/t...ganizacniJednotka
  • 23520
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