Computer Vision for Hand Gestures

Jonas Robin, Mehul Soni, Rishabh Rajkumar Dubey, Nimish Arvind Datkhile, J. Kolap
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Abstract

The model developed here is used to detect specific items from the environment. The desired objects to be detected from the environment is hands(gestures). So, for computer to look at the environment computer vision is the most necessary aspect. Based, on the gesture present in the image captured along with the unnecessary objects, the image is processed and the important message is kept and rest is discarded. After processing the neural networks are introduced for to elevate the standards of computer vision there by allowing computer to know about the gesture provided by the humans. Here the recognition of the image is done by using Convolution neural network (CNN) algorithm, the gesture is predicted and this predicted result is shown on the screen connected or an audio device connected.
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手势的计算机视觉
这里开发的模型用于从环境中检测特定项目。从环境中检测到的期望对象是手(手势)。所以,对于计算机来说,看环境是计算机视觉最必要的方面。基于捕捉到的图像中存在的手势以及不必要的物体,对图像进行处理,保留重要的信息,丢弃其余信息。经过处理后,引入神经网络,使计算机能够了解人类提供的手势,从而提高计算机视觉的水平。这里使用卷积神经网络(CNN)算法对图像进行识别,对手势进行预测,并将预测结果显示在连接的屏幕或连接的音频设备上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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