基于Leap Motion的缅甸手语识别使用机器学习

Zaw Hein, Thet Htoo, Bawin Aye, Sai Myo Htet, Kyaw Zaw Ye
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引用次数: 3

摘要

手语是聋哑人的主要交流语言。聋哑人与正常人交流有很多困难。只有少数人能熟练地使用手语,大多数人不知道如何与聋哑人交流。从计算机视觉的角度出发,我们可以开发聋哑人的手语识别。大多数的手语识别系统都是基于静态符号的。在基于动作的手语识别系统中,提出了特征提取方法和机器学习识别方法。每个国家都有自己的手语,我们提出的系统是基于缅甸国家手语。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leap Motion based Myanmar Sign Language Recognition using Machine Learning
Sign language is the main communication language for deaf and dumb people. There have many difficulties for deaf and dumb people when they communicate with normal people. Only a few people can use Sign Language proficiently and most of the people don’t know how to communicate the deaf people. From the point of view of computer vision, we can develop the sign language recognition for deaf and dumb people. Most of the sign language recognition systems are based on the static sign. In motion-based sign language recognition system, we proposed feature extraction method and recognition using machine learning. Every nation has its own sign language and our proposed system is based on Myanmar National Sign Language.
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