Abstract: The main aim of this system is to predict and analyze gesture pattern from a user based on machine learning. The system is adopted in the rock-paper-scissors game which is suggested as always win at the game by predicting user gesture. Quantization and processing of user gesture from EMG sensor are implemented to generate training data in order that disciplining machine. As suggested procedure, an enormous amount of user gesture data will be collected and training model will be implemented with machine learning. By adopting the implemented system into the game, the research will verify that it is feasible to predict user gesture during playing game. The manner of a game is that computer shows the result when the user starts the rock-paper-scissors game in front of the monitor and the system always shows winning result that is the main purpose of it.

• Publication Date: 26-Feb-2017
• DOI: 10.15224/978-1-63248-117-7-57
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Abstract: Recently, a variety of businesses have appeared not only in the drone's military market but also in the consumer market and the service market. The reason for the rapid growth of the market is that it is possible to produce cheap drones using open source. Although there are lots of system for controlling drones, people still experience accidents due to inexperienced user who purchased drones. These accidents occur from the difference between the viewpoint of the user and the drones. Therefore, in this paper, we propose a User Centric Drone Controller (UCDC) to reduce accidents caused by clumsy manipulation.

• Publication Date: 26-Feb-2017
• DOI: 10.15224/978-1-63248-117-7-58
• Views: 0
• Downloads: 0