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All Journal Jurnal ULTIMA Computing
Aurelius Ryo
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Computer Science & IT Control & Systems Engineering Engineering

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Hand Gesture Detection for Sign Language using Neural Network with Mediapipe Arsheldy Alvin; Nabila Husna Shabrina; Aurelius Ryo; Edgar Christian
Ultima Computing : Jurnal Sistem Komputer Vol 13 No 2 (2021): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v13i2.2109

Abstract

The most popular way of interfacing with most computer systems is a mouse and keyboard. Hand gestures are an intuitive and effective touchless way to interact with computer systems. However, hand gesture-based systems have seen low adoption among end-users primarily due to numerous technical hurdles in detecting in-air gestures accurately. This paper presents Hand Gesture Detection for American Sign Language using K-Nearest Neighbor with Mediapipe, a framework developed to bridge this gap. The framework learns to detect gestures from demonstrations, it is customizable by end-users, and enables users to interact in real-time with computers having only RGB cameras, using gestures.
Co-Authors Arsheldy Alvin Edgar Christian Shabrina, Nabila Husna