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Topical Summarization Of Web Videos By Visual-Text Time-Dependent Alignment, Song Tan, Hung-Khoon Tan, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Search engines are used to return a long list of hundreds or even thousands of videos in response to a query topic. Efficient navigation of videos becomes difficult and users often need to painstakingly explore the search list for a gist of the search result. This paper addresses the challenge of topical summarization by providing a timeline-based visualization of videos through matching of heterogeneous sources. To overcome the so called sparse-text problem of web videos, auxiliary information from Google context is exploited. Google Trends is used to predict the milestone events of a topic. Meanwhile, the typical scenes of web …