A Gesture Recognition Based on Accelerometer and Hidden Markov Model for Human Computer Communication

Abstract:

Along with the continuous changes and improvement of information technology, remote controls are widely used in smart living, robot control, Sign language systems, and so on. However, the human-computer communication needs to be diversified in the future. In particular, users are not intuitive when applying a special application or remote control environment, thus, this study applying Nintendo Wii remote as a human-computer interface device, to capture motion data by built-in three-axis accelerometer sensor, and training and recognize with Hidden Markov Model. First, we apply a gesture recognize system, to enhance the interactive ability of three-axis accelerometer sensor, gesture commands are trainable by user on-demand, and users can interactive with different computer applications through the gesture command has been trained. Finally, this study had issued a Gesture Recognition approach for intelligent interactive system design and for future study.

• Periodical: Applied Mechanics and Materials (Volumes 479-480)
• Pages: 938-942
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.479-480.938
• Online since: December 2013
• Authors: Shu Lin Wang, Zhe George Zhang, You Gang Guo
• Keywords: Accelerometer, Gesture Recognition, Hidden Markov Model (HMM), Human Computer Communication, Human-Computer Interaction (HCI)

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