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Uses a raspberry pi camera or web cam and python opencv to track motion in camera view. Sends motion contour data to sonic-pi via osc interface to produce and control notes/sample. Includes ability to use onscreen menu areas to change synthesizer, octaves Etc.
This project explores user authentication on mobile devices through typing patterns, leveraging touch and motion data. Using machine learning models, particularly LSTM, the research demonstrates superior user classification accuracy compared to traditional RNN models, enhancing security against ATO attacks.