Dynamic Hand Gesture to Text using Leap Motion

被引:0
|
作者
Jamaludin, Nur Aliah Nadzirah [1 ]
Fang, Ong Huey [2 ]
机构
[1] Univ Malaysia Comp Sci & Engn, Fac Comp, Cyberjaya, Selangor, Malaysia
[2] Monash Univ Malaysia, Sch Informat Technol, Bandar Sunway, Selangor, Malaysia
关键词
Dynamic hand gesture; leap motion; American sign language; artificial neural network; cross-correlation; geometric template matching;
D O I
10.14569/IJACSA.2019.0101127
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
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.
引用
收藏
页码:199 / 204
页数:6
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