引出用户对视频摘要的个性化解释的偏好

O. Inel, N. Tintarev, Lora Aroyo
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引用次数: 5

摘要

视频摘要或亮点是探索和背景化前所未有的视频材料的一个引人注目的选择。然而,总结过程通常是自动的,不透明的,并且可能偏向于原始视频中描述的特定方面。因此,我们的目标是帮助像档案管理员或收藏管理员这样的用户快速了解哪些摘要是最具代表性的原始视频。在本文中,我们提出了关于不同类型的视觉解释的效用的实证结果,以实现最终用户对代表性视频摘要相对于原始视频的透明度。我们考虑了四种类型的视频摘要解释,它们以不同的方式使用从原始视频字幕和视频流中提取的概念,以及它们的突出性。这些解释是为了满足目标用户的偏好而生成的,并表达了透明度的不同维度:概念突出性、语义覆盖、覆盖距离和覆盖数量。在两个用户研究中,我们评估了可视化解释对最终用户实现透明度的效用。我们的结果表明,代表所有维度的解释对于透明度具有最高的效用,因此对于理解视频摘要的代表性也具有最高的效用。
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Eliciting User Preferences for Personalized Explanations for Video Summaries
Video summaries or highlights are a compelling alternative for exploring and contextualizing unprecedented amounts of video material. However, the summarization process is commonly automatic, non-transparent and potentially biased towards particular aspects depicted in the original video. Therefore, our aim is to help users like archivists or collection managers to quickly understand which summaries are the most representative for an original video. In this paper, we present empirical results on the utility of different types of visual explanations to achieve transparency for end users on how representative video summaries are, with respect to the original video. We consider four types of video summary explanations, which use in different ways the concepts extracted from the original video subtitles and the video stream, and their prominence. The explanations are generated to meet target user preferences and express different dimensions of transparency: concept prominence, semantic coverage, distance and quantity of coverage. In two user studies we evaluate the utility of the visual explanations for achieving transparency for end users. Our results show that explanations representing all of the dimensions have the highest utility for transparency, and consequently, for understanding the representativeness of video summaries.
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