An Image Classification-based Approach to Automate Video Playing Detection at System Level

Eric Liu, Samuel Walcoff, Qiuli Lu, Yu Sun
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Abstract

Tech distraction has become a critical issue on people’s work and study productivity, particularly with the growing amount of digital content from the social media site such as Youtube. Although browser-based plug-ins are available to help block and monitor the sites, they do not work for all scenarios. In this paper, we present a system-level video playing detection engine that captures screenshots and analyze the screenshot image using deep learning, in order to predict whether the image has videos in it or not. A mobile app has also been developed to enable parents to control the video playing detection remotely.
基于图像分类的系统级自动视频播放检测方法
科技分心已经成为影响人们工作和学习效率的一个关键问题,尤其是随着Youtube等社交媒体网站上的数字内容越来越多。尽管基于浏览器的插件可用于帮助阻止和监视站点,但它们并不适用于所有场景。在本文中,我们提出了一个系统级的视频播放检测引擎,该引擎捕获截图并使用深度学习分析截图图像,以预测图像中是否含有视频。该公司还开发了一款手机应用程序,使家长能够远程控制视频播放检测。
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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