Preliminary result on gesture recognition of Sigeh Penguten Dance using Hidden Markov Model

Autor: Ary Setijadi Prihatmanto, Aciek Ida Wuryandari, Maria Shusanti Febrianti, Carmadi Machbub, Egi Hidayat
Rok vydání: 2016
Předmět:
Zdroj: ICSET
DOI: 10.1109/icsengt.2016.7849644
Popis: In this paper, an implementation of gesture recognition using Hidden Markov Model to classify particular gestures on Sigeh Penguten traditional Dance is presented. The preliminary research is focused on recognition of dancers' hand gestures, i.e. ‘Sembah Depan’, ‘Sembah Kiri’, and ‘Sembah Kanan’ gestures based on their collected hands marker positions. The experimental results show that the proposed approach is able to classify the three mentioned gestures even with only the hands' positions to a certain degree. However, the reliability of the proposed approach requires further improvement.
Databáze: OpenAIRE