Video composition by the crowd: a system to compose user-generated videos in near real-time

Stefan Wilk, S. Kopf, W. Effelsberg
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引用次数: 15

Abstract

To compose high-quality movies directors need life-long learning and talent. User-generated video defines a new era of video production in which non-professionals record videos and share them on platforms such as YouTube. As hiring professional directors results in high costs, our work focuses on replacing those directors by crowdsourcing. The proposed system allows users to record and stream live videos to servers on which workers create a video mashup. A smartphone application for recording live video has been designed that supports the composition in the crowd by a multi-modal analysis of the recording quality. The contributions of this work are: The proposed system demonstrates that composing a large number of video views can be achieved in near real-time. Second, the system achieves comparable video quality for user-generated video in comparison to manual composition. Third, it offers insights on how to design real-time capable crowdsourcing systems. Fourth, by leveraging multi-modal features that can already be evaluated during recording the number of streams considered for presentation can be reduced.
人群视频合成:一个近乎实时地合成用户生成视频的系统
要创作出高质量的电影,导演需要终身学习和才能。用户生成视频定义了一个视频制作的新时代,非专业人士录制视频并在YouTube等平台上分享。由于聘请专业董事的成本很高,我们的工作重点是通过众包的方式替换这些董事。提议的系统允许用户录制并将直播视频流到服务器上,工作人员可以在服务器上创建视频混搭。设计了一款用于录制现场视频的智能手机应用程序,通过对录制质量的多模态分析来支持人群中的构图。本研究的贡献在于:该系统证明了在近实时的情况下可以实现大量视频视图的合成。其次,与人工合成相比,该系统实现了与用户生成视频相当的视频质量。第三,它提供了如何设计实时能力的众包系统的见解。第四,通过利用在记录过程中已经可以评估的多模态特性,可以减少考虑用于呈现的流的数量。
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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