Abstract:Huge amount of videos on the Internet have rare textual information, which makes video retrieval challenging given a text query. Previous work explored semantic concepts for content analysis to assist retrieval. However, the humandefined concepts might fail to cover the data and there is a potential gap between these concepts and the semantics expected from user's query. Also, building a corpus is expensive and time-consuming. To address these issues, we propose a semi-automatic framework to discover the seman… Show more
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