基于深度学习的手势翻译系统

S. Shareef, I. Haritha, Y. Prasanna, Manish Kumar
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引用次数: 4

摘要

手语在聋哑人之间的非语言交流中起着重要的作用。对于Kinetics公司来说,手势在我们的日常生活中起着至关重要的作用。有不同的手语可用,手势翻译是其中之一。手语是不同手势符号的集合,每个手势符号都有其特殊的含义。它主要用于聋哑人与正常人快速表达自己的观点和想法。该系统的主要问题是翻译符号非常困难,需要对手语进行特殊培训。为了克服这个问题,我们实现了一个手势翻译系统,它提供了与机器有效交互的能力。它将帮助聋哑人更有效地与正常人表达他们的感受和观点。本文实现了一种能够自动识别手势的软件原型,准确率达到93.4%,用于手势翻译,帮助聋哑人轻松与正常人进行互动。该项目的主要目的是通过手势为正常人和聋哑人之间提供一种简单的沟通方式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deep Learning Based Hand Gesture Translation System
Sign language plays an important role for the people who have the hearing and speech problems For the Non-verbal communication between the deaf-mute people. For the Kinetics gestures plays a crucial role in our day-to-day life. There are different sign languages that are available Hand Gesture Translation is one among them. The sign language is a collection of different Hand Gesture symbols and Each Hand Gesture symbol have special meaning. It is mostly used by the deaf-mute persons to express their views and thoughts very quickly with the normal people. Main problem with this system is very difficult to translate the symbols and required special training on sign language. To overcome this problem we have implemented a Hand Gesture Translation System it provides an ability to interact with the machine efficiently. It will help the deaf-mute to express their feelings and views more effectively with the normal people. In this paper implemented software prototype that will automatically recognize the hand gestures with an accuracy of 93.4% for gesture Translation which will help the deaf and dumb people to interact easily with the normal people. The main aim of the project is to provide the easy way of communication between the normal people and the deaf-mute through gestures.
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