Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

12-2010

Abstract

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 videos are extracted by visual near-duplicate threading. Visual-text alignment is then conducted to align scenes from videos and articles from Google News. The outcome is a set of scene-news pairs, each representing an event mapped to the milestone timeline of a topic. The timeline-based visualization provides a glimpse of major events about a topic. We conduct both the quantitative and subject

Keywords

Google context, timeline-based summarization

Discipline

Data Storage Systems | Theory and Algorithms

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of the 18th ACM International Conference on Multimedia ACM Multimedia, MM2010, Firenze, Italy, October 25-29

First Page

1095

Last Page

1098

ISBN

9781605589336

Identifier

10.1145/1873951.1874159

Publisher

ACM

City or Country

Firenze, Italy

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