残疾人用手势控制视频

Stella Nadar, Simran Nazareth, K. Paulson, Nilambri Narkar
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引用次数: 0

摘要

在众多基于计算机视觉的交互系统中,设计基于手势和面部表情的人机交互(HCI)系统一直是一项极具挑战性的任务。我们的主要目的是找到一种与计算机交互的无形方式。我们的项目旨在利用卷积神经网络(CNN)开发一个由人类手势控制的视频播放器。这些手势将作为播放或暂停视频等操作的直接命令。它使用简单的手势来控制视频。因此,人们不需要学习像机器一样的技能,只需要记住一组手势来控制视频播放。关键词:机器学习,CNN(卷积神经网络),开放式简历,分类模型,网络摄像头
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VIDEO CONTROLLING USING HAND GESTURES FOR DISABLED PEOPLE
Among many computer visions based interactive systems, designing hand gesture and facial expression based Human-Computer-Interaction (HCI) system retains to be a highly challenging task. Our main purpose is to find a non-tangible way to interact with the computer. Our project aims at developing a video-player controlled by the human hand gestures by making use of Convolutional Neural Network (CNN). The gestures would serve as the direct command for operations such as play or pause the video. It uses simple gestures to control the video. So people don’t have to learn the machine like skills and only need to remember a set of gestures to control the video playback. Keywords—: Machine Learning, CNN (Convolutional Neural Network), Open CV, Classification model, webcam.
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