Advanced gesture recognition system using long-term recurrent convolution network
Advanced gesture recognition system using long-term recurrent convolution network
复制标题
使用长期循环卷积网络的高级手势识别系统
DOI：
10.1016/j.matpr.2019.06.748
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
A. Manjunathan
中科院分区：
文献类型：
--
作者：
C. Bhuvaneshwari;A. Manjunathan
聋哑人与正常人之间的可靠交流是困难的，因为聋哑人使用手语进行交流，而正常人是不知道的。在这项研究工作中，为聋哑人所面临的问题提供解决方案。它涉及到手势图像识别的想法。本文将嵌入式系统和图像处理的概念结合在一起，非常有效。该设备将手势图像转换为语音。使用Raspberry Pi进行转换。采用LRCN（Long-term Recurrent Convolution Network）算法对手势图像进行识别。
The reliable communication between deaf-dumb and normal people is difficult, because deaf and dumb people use sign language for their communication which is unknown to the normal person. In this research work, to provides solution for problem faced by deaf and dumb people. It deals with an idea of gesture image recognition. In this the concept of embedded system and image processing is combined together which is very effective. This device convert gesture image to voice. The conversion is done using Raspberry pi. Gesture image recognition is processed by implementing LRCN (Long-term Recurrent Convolution Network) algorithm.