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An End-to-End Scalable Copyright Detection System for Online Video Sharing Platforms

机译:在线视频共享平台的端到端可扩展版权检测系统

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Combating copyright infringing multimedia content has arisen as a critical undertaking in online video sharing platforms, such as YouTube and Twitch. In contrast to the traditional copyright detection problem that studies the static content (e.g., music, films, digital documents), the proposed system focuses on a much more challenging problem: detecting copyright infringements in live video streams. This is motivated by the observation that a large amount of copyright-infringing videos bypass the detector while many legal videos are taken down by mistake. In this paper, we present an end-to-end system that is dedicated to combating the copyright infringements in live video streams. The system to be demonstrated consists of 1) a web front-end for user interaction and customized video query, 2) a scalable and real-time video crawling system that can collect video metadata, live chat messages, and visual content of the live video streams on video sharing platforms, and 3) a novel supervised copyright detection engine that leverages the live chat messages of the audience to detect the copyright infringement of live videos.
机译:在诸如YouTube和Twitch之类的在线视频共享平台上,打击侵犯版权的多媒体内容已成为一项关键任务。与研究静态内容(例如音乐,电影,数字文档)的传统版权检测问题相比,拟议的系统着重于更具挑战性的问题:检测实时视频流中的版权侵权。观察到的动机是,大量侵犯版权的视频绕过了检测器,而许多合法视频却被错误地删除。在本文中,我们提出了一个端到端系统,该系统致力于解决实况视频流中的版权侵权问题。待演示的系统包括1)用于用户交互和自定义视频查询的Web前端,2)可伸缩的实时视频爬网系统,可以收集视频元数据,实时聊天消息和实时视频的可视内容在视频共享平台上流式传输,以及3)一种新颖的受监督的版权检测引擎,该引擎利用受众的实时聊天消息来检测实时视频的版权侵权。

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