论文标题
引起用户偏好的个性化解释视频摘要
Eliciting User Preferences for Personalized Explanations for Video Summaries
论文作者
论文摘要
视频摘要或亮点是探索和上下文化的前所未有的视频材料的引人注目的替代方法。但是,汇总过程通常是自动的,非透明的,并且可能偏向原始视频中描述的特定方面。因此,我们的目的是帮助档案管理员或收集经理等用户快速了解哪些摘要是原始视频最具代表性的摘要。在本文中,我们介绍了有关不同类型的视觉解释的实用性,以实现最终用户在代表性视频摘要方面的透明度,相对于原始视频。我们考虑了四种类型的视频摘要说明,它们以不同的方式使用了原始视频字幕和视频流的概念及其突出。生成的解释是为了满足目标用户的偏好并表达透明度的不同维度:概念突出,语义覆盖,距离,距离和覆盖范围。在两项用户研究中,我们评估了视觉解释的实用性,以实现最终用户的透明度。我们的结果表明,代表所有维度的解释具有最高的透明度效用,因此可以理解视频摘要的代表性。
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.