Multimodal Video-to-Video Linking: Turning to the Crowd for Insight and Evaluation

详细信息    查看全文

• 关键词：Crowdsourcing ; Video ; to ; video linking ; Link evaluation ; Verbal ; visual information
• 刊名：Lecture Notes in Computer Science
• 出版年：2017
• 出版时间：2017
• 年：2017
• 卷：10133
• 期：1
• 页码：280-292
• 丛书名：MultiMedia Modeling
• ISBN：978-3-319-51814-5
• 卷排序：10133

文摘

Video-to-video linking systems allow users to explore and exploit the content of a large-scale multimedia collection interactively and without the need to formulate specific queries. We present a short introduction to video-to-video linking (also called ‘video hyperlinking’), and describe the latest edition of the Video Hyperlinking (LNK) task at TRECVid 2016. The emphasis of the LNK task in 2016 is on multimodality as used by videomakers to communicate their intended message. Crowdsourcing makes three critical contributions to the LNK task. First, it allows us to verify the multimodal nature of the anchors (queries) used in the task. Second, it enables us to evaluate the performance of video-to-video linking systems at large scale. Third, it gives us insights into how people understand the relevance relationship between two linked video segments. These insights are valuable since the relationship between video segments can manifest itself at different levels of abstraction.