Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

11-2012

Abstract

Associating celebrity faces appearing in videos with their names is of increasingly importance with the popularity of both celebrity videos and related queries. However, the problem is not yet seriously studied in Web video domain. This paper proposes a Community connected Celebrity Name-Face Association approach (CCNFA), where the community is regarded as an intermediate connector to facilitate the association. Specifically, with the names and faces extracted from Web videos, C-CNFA decomposes the association task into a three-step framework: community discovering, community matching and celebrity face tagging. To achieve the goal of efficient name-face association under this umbrella, algorithms such as the constrained density-based clustering and exemplar based voting are developed by leveraging different pieces of visual and contextual cues. The evaluation on 0.4 million faces and 144 celebrities shows the effectiveness of the proposed C-CNFA approach. Moreover, using the obtained associations, encouraging results are reported in celebrity video ranking.

Keywords

celebrity videos, community analysis, name-face association

Discipline

Data Storage Systems | Graphics and Human Computer Interfaces

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of the 20th ACM international conference on Multimedia, MM 2012, Nara, Japan, October 29 - November 2

First Page

809

Last Page

812

ISBN

9781450310895

Identifier

10.1145/2393347.2396318

Publisher

ACM

City or Country

Nara, Japan

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