Real time isolated turkish sign language recognition from video using Hidden Markov models with global features

HABERDAR H., VARLI S.

20th International Symposium on Computer and Information Sciences, ISCIS 2005, İstanbul, Türkiye, 26 - 28 Ekim 2005, cilt.3733 LNCS, ss.677-687, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 3733 LNCS
  • Doi Numarası: 10.1007/11569596_70
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.677-687
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

This paper introduces a video based system that recognizes gestures of Turkish Sign Language (TSL). Hidden Markov Models (HMMs) have been applied to design a sign language recognizer because of the fact that HMMs seem ideal technology for gesture recognition due to its ability of handling dynamic motion. It is seen that sampling only four key-frames is enough to detect the gesture. Concentrating only on the global features of the generated signs, the system achieves a word accuracy of 95.7%. © Springer-Verlag Berlin Heidelberg 2005.