Publication Type

Journal Article

Publication Date

2-2016

Abstract

Accurate video tagging has been becoming increasingly crucial for online video management and search. This article documents a novel framework called comprehensive video tagger (CVTagger) to facilitate accurate tag-based video annotation. The system applies both multimodal and temporal properties combined with a novel classification framework with hierarchical structure based on multilayer concept model and regression analysis. The advanced architecture enables effective incorporation of both video concept dependency and temporal dynamics. Using a large-scale test collection containing 50,000 YouTube videos, a set of empirical studies have been carried out and experimental results demonstrate various advantages of CVTagger over the state-of-the-art techniques.

Keywords

Online video, Social multimedia, Tagging

Discipline

Computer Sciences | Databases and Information Systems

Research Areas

Data Management and Analytics

Publication

Multimedia Systems

Volume

22

Issue

1

First Page

99

Last Page

113

ISSN

0942-4962

Identifier

10.1007/s00530-014-0399-4

Publisher

Springer Verlag

Additional URL

http://dx.doi.org/10.1007/s00530-014-0399-4

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