Large scale news video database browsing and retrieval via information visualization

作     者：Luo, Hangzai Fan, Jianping Satoh, Shin'Ichi Ribarsky, William 

作者机构：Dept. of Computer Science UNC-Charlotte Charlotte NC 28223 United States National Inst. of Informatics Tokyo Japan 

出 版 物：《Proceedings of the ACM Symposium on Applied Computing》 

年 卷 期：2007年

页      面：1086-1087页

核心收录：

主　　题：Information retrieval 

摘      要：In this paper, we have developed a novel framework to enable more effective visual analysis and retrieval of large-scale news videos via interactive visualization, so that the audiences can find news stories of interest at first glance. Keyframes and keywords are automatically extracted from news video clips and visually represented according to their interestingness measurement and relations. A computational approach is also developed to quantify the interestingness measurement of video clips. Our experimental results have shown that our techniques for intelligent news video analysis have the capacity to enable more effective visualization and retrieval of large-scale news videos. Our visualization-based news video analysis and retrieval system is very useful for security applications and for general audiences to quickly find the news stories of interest from large-scale news videos among many channels. Copyright 2007 ACM.