Dynamic Hand Gesture to Text using Leap Motion

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...

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Bibliographic Details
Published inInternational journal of advanced computer science & applications Vol. 10; no. 11
Main Authors Jamaludin, Nur Aliah Nadzirah, Huey, Ong
Format Journal Article
LanguageEnglish
Published West Yorkshire Science and Information (SAI) Organization Limited 2019
Subjects
Accuracy
Algorithms
Artificial neural networks
Cameras
Computer science
Cross correlation
Gloves
Neural networks
Prototypes
Recognition
Sign language
Template matching
Training
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Summary: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.
ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2019.0101127