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Title:
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A INTERFACING CONTROLLER FOR GAMES BASED ON GESTURE RECOGNITION |
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Author(s):
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Ivo A. Stinghen Filho, Bernardo B. Gatto, Jose Luiz de S. Pio, Estevam N. Chen, Jucimar M. Junior and Ricardo Barboza |
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ISBN:
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978-989-8533-82-1 |
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Editors:
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Pedro Isaías and Hans Weghorn |
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Year:
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2018 |
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Edition:
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Single |
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Keywords:
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Virtual Reality, Leap Motion, Motion Capture, Machine Learning |
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Type:
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Full Paper |
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First Page:
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329 |
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Last Page:
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336 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Theres a developing propensity of using of real-time interactions and changing over the signals to the virtual situations. In this paper, we show a gesture interfacing controller for real-time communication between the Leap Motion sensor and games. Combined to this, we do compare the adequacy of different algorithms of machine learning calculations for real-time hand gesture recognition to discover the foremost ideal way to identify static hand gestures, as well as the foremost ideal sample size for utilizing in the training step of the calculations. Additionally, we present a novel in-active hand signal data set containing 1200 tests for 10 inactive motion classes. In our system, Leap Motion and Unity were utilized to extricate the information. And the training was done using Python and scikit-learn. To evaluate our gesture interfacing controller effectiveness, we made a demonstration game scene where 12 people. |
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