Classification and skimming of articles for an effective news browsing

Authors:
Jungwon Cho;Seungdo Jeong;Byunguk Choi
Affiliations:
Department of Computer Education, College of Education, Cheju National University, Jeju-si, Jeju-do, Korea;Multimedia Laboratory, Department of Electrical and Computer Engineering, Hanyang University, Seoul, Korea;Division of Information and Communications, Hanyang University, Seoul, Korea
Venue:
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Year:
2005

Citing 6
Cited 0

Video parsing, retrieval and browsing: an integrated and content-based solution

Intelligent multimedia information retrieval
Informedia: news-on-demand multimedia information acquisition and retrieval

Intelligent multimedia information retrieval
Adjustable Filmstrips and Skims as Abstractions for a Digital Video Library

ADL '99 Proceedings of the IEEE Forum on Research and Technology Advances in Digital Libraries
Video Skimming and Characterization through the Combination of Image and Language Understanding

CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
Time-Constrained Keyframe Selection Technique

ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Automatic Classification of Tv News Articles Based on Telop Character Recognition

ICMCS '99 Proceedings of the 1999 IEEE International Conference on Multimedia Computing and Systems - Volume 02

Quantified Score

Hi-index	0.00

Visualization

Abstract

In order to browse the news video effectively, classification and skimming of news articles are positively essential. In this paper, we propose the classification and skimming of articles for an effective news browsing. The classification method uses tags to distinguish speakers in the closed-caption. The skimming method extracts the representative sentence from the part of article introduced by the anchor in the closed-caption and the representative frames consisting of anchor frame, open-caption frames, and frames synchronized with high-frequency terms. In the experiment, we have applied the proposed classification and skimming methods to news video with Korean closed-captions, and have empirically confirmed that the proposed methods could support effective browsing of news videos.