Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

9-2007

Abstract

Current web video search results rely exclusively on text keywords or user-supplied tags. A search on typical popular video often returns many duplicate and near-duplicate videos in the top results. This paper outlines ways to cluster and filter out the nearduplicate video using a hierarchical approach. Initial triage is performed using fast signatures derived from color histograms. Only when a video cannot be clearly classified as novel or nearduplicate using global signatures, we apply a more expensive local feature based near-duplicate detection which provides very accurate duplicate analysis through more costly computation. The results of 24 queries in a data set of 12,790 videos retrieved from Google, Yahoo! and YouTube show that this hierarchical approach can dramatically reduce redundant video displayed to the user in the top result set, at relatively small computational cost.

Keywords

Copy selection, Filtering; Multimodality, Near-duplicates, Novelty and redundancy detection, Similarity measure, Web video

Discipline

Data Storage Systems | Graphics and Human Computer Interfaces

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of the 15th ACM International Conference on Multimedia, MM2007, Augsburg, Bavaria, September 23-28

First Page

218

Last Page

227

ISBN

9781595937025

Identifier

10.1145/1291233.1291280

Publisher

ACM

City or Country

Augsburg, Bavaria

Download

Share

COinS