Arduino Based Motion Tracking Keyboard Using Machine Learning
Arduino Based Motion Tracking Keyboard Using Machine Learning
- Neue Suche nach: Aditya Priyadarshi
- Neue Suche nach: Bharath V
- Neue Suche nach: Aptha KS
- Neue Suche nach: Sanjit S
- Neue Suche nach: Sahana V
- Neue Suche nach: Aditya Priyadarshi
- Neue Suche nach: Bharath V
- Neue Suche nach: Aptha KS
- Neue Suche nach: Sanjit S
- Neue Suche nach: Sahana V
In spite of the emergence of various sensors and input devices, the current methods have not been able to provide an accurate recognition system for gestures. Recognition system such as the one in Kinect using machine learning algorithms shows some of the use cases for these gestures to newer system and domains. The one in our paper provides a far more accurate result along with faster computational speed as it uses the support vector machine (SVM) algorithm. This motion recognition system tracks motion made in mid-air by device in a 3D space, log its speed, angular velocity, distance covered and some other variables at real time, and in turn convert the device captured data of motion into characters of English alphabets. The device presented in this paper presents solution based on support vector algorithms and discusses about some concepts raised from the device.
Dokumentinformationen
Arduino Based Motion Tracking Keyboard Using Machine Learning
2019-07-04
oai:zenodo.org:3268229
Journal of Data Mining and Management 4(2) 9-14
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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