Title :
The study of feature vector in HMM-based Wii application for Thai sword dance
Author :
Sanpechuda, T. ; Kovavisaruch, L. ; Chinda, K. ; Chaiwongyen, A. ; Wisadsud, S. ; Wongsatho, T. ; Charoenporn, T.
Author_Institution :
Nat. Electron. & Comput. Technol. Center, Pathumthani, Thailand
Abstract :
In beginning to classify gestures, a Wii remote is used as the primary tool for collecting raw data. Next, the Hidden Markov Model method is used to classify the gestures. The performance of this classification method is reliant on the feature vector used. In this paper, we will propose an appropriate feature vector for classifying gestures used in Thai sword dancing. The feature vectors are evaluated for their accuracy of classification based on their receptivity to acceleration, velocity, and displacement.
Keywords :
hidden Markov models; humanities; image classification; HMM-based Wii application; Thai sword dance; acceleration; displacement; feature vector; gesture classification; hidden Markov model method; raw data collection; velocity; Artificial intelligence; Bismuth; Hidden Markov models; Support vector machine classification; Classification; Gesture; HMM; Thai sword dance; Wii remote; feature vector;
Conference_Titel :
Intelligent Signal Processing and Communications Systems (ISPACS), 2011 International Symposium on
Conference_Location :
Chiang Mai
Print_ISBN :
978-1-4577-2165-6
DOI :
10.1109/ISPACS.2011.6146117
