Publication Type

Journal Article

Version

publishedVersion

Publication Date

2-2009

Abstract

With the exponential growth of social media, there exist huge numbers of near-duplicate web videos, ranging from simple formatting to complex mixture of different editing effects. In addition to the abundant video content, the social web provides rich sets of context information associated with web videos, such as thumbnail image, time duration and so on. At the same time, the popularity of Web 2.0 demands for timely response to user queries. To balance the speed and accuracy aspects, in this paper, we combine the contextual information from time duration, number of views, and thumbnail images with the content analysis derived from color and local points to achieve real-time near-duplicate elimination. The results of 24 popular queries retrieved from You Tube show that the proposed approach integrating content and context can reach real-time novelty re-ranking of web videos with extremely high efficiency, where the majority of duplicates can be rapidly detected and removed from the top rankings. The speedup of the proposed approach can reach 164 times faster than the effective hierarchical method proposed in [31], with just a slight loss of performance.

Keywords

Content, context, copy detection, filtering, near-duplicates, novelty and redundancy detection, similarity measure, web video

Discipline

Graphics and Human Computer Interfaces

Research Areas

Intelligent Systems and Optimization

Publication

IEEE Transactions on Multimedia

Volume

11

Issue

2

First Page

196

Last Page

207

ISSN

1520-9210

Identifier

10.1109/TMM.2008.2009673

Publisher

Institute of Electrical and Electronics Engineers

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