Abstract: This paper presents a prototype for converting dynamic hand gestures to text by using a device called Leap Motion. It is one of the motion tracking technologies, which could be used for recognising hand gestures without the need of wearing any external devices or capturing any images and videos. In this study, five custom dynamic hand gestures of American Sign Language were created with Leap Motion to measure the recognition accuracy of the proposed prototype using the Geometric Template Matching, Artificial Neural Network, and Cross-Correlation algorithms. The experimental results showed that the prototype achieved recognition accuracy of more than 90% in the training phase and about 60% in the testing phase.

Nur Aliah Nadzirah Jamaludin and Ong Huey Fang, “Dynamic Hand Gesture to Text using Leap Motion” International Journal of Advanced Computer Science and Applications(IJACSA), 10(11), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101127

@article{Jamaludin2019,
title = {Dynamic Hand Gesture to Text using Leap Motion},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2019.0101127},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101127},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {11},
author = {Nur Aliah Nadzirah Jamaludin and Ong Huey Fang},
}