Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

7-2003

Abstract

In this paper, a novel approach for automatic matching, ranking and retrieval of video clips is proposed. Motivated by the maximal and optimal matching theories in graph analysis, a new similarity measure of video clips is defined based on the representation and modeling of bipartite graph. Four different factors: visual similarity, granularity, interference and temporal order of shots are taken into consideration for similarity ranking. These factors are progressively analyzed in the proposed approach. Maximal matching utilizes the granularity factor to efficiently filter false matches, while optimal matching takes into account the visual, granularity and interference factors for similarity measure. Dynamic programming is also formulated to quantitatively evaluate the temporal order of shots. The final similarity measure is based on the results of optimal matching and dynamic programming. Experimental results indicate that the proposed approach is effective and efficient in retrieving and ranking similar video clips.

Discipline

Computer Sciences | Graphics and Human Computer Interfaces

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of 2003 International Conference on Multimedia and Expo, Baltimore, Maryland, July 6-9

Volume

1

First Page

317

Last Page

320

ISBN

0780379659

Identifier

10.1109/ICME.2003.1220918

Publisher

IEEE Computer Society

City or Country

Baltimore

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