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arXiv · 1705.05884

Static Gesture Recognition using Leap Motion

Babak Toghiani-Rizi·Christofer Lind·Maria Svensson·Marcus Windmark
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Abstract

In this report, an automated bartender system was developed for making orders in a bar using hand gestures. The gesture recognition of the system was developed using Machine Learning techniques, where the model was trained to classify gestures using collected data. The final model used in the system reached an average accuracy of 95%. The system raised ethical concerns both in terms of user interaction and having such a system in a real world scenario, but it could initially work as a complement to a real bartender.

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BibTeXRIS

Babak Toghiani-Rizi, Christofer Lind, Maria Svensson, Marcus Windmark. 2017-05-16. Static Gesture Recognition using Leap Motion. https://arxiv.org/abs/1705.05884

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