Real time isolated Turkish Sign Language recognition from video using Hidden Markov Models with global features

Haberdar H., VARLI S.

COMPUTER AND INFORMATION SCIENCES - ISCIS 2005, PROCEEDINGS, cilt.3733, ss.677-687, 2005 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 3733
  • Basım Tarihi: 2005
  • Dergi Adı: COMPUTER AND INFORMATION SCIENCES - ISCIS 2005, PROCEEDINGS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED)
  • Sayfa Sayıları: ss.677-687
  • Yıldız Teknik Üniversitesi Adresli: Hayır

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%.