Title :
Exploring Large-Scale Video News via Interactive Visualization
Author :
Luo, Hangzai ; Fan, Jianping ; Yang, Jing ; Ribarsky, William ; Satoh, Shin Ichi
Author_Institution :
Dept. of Comput. Sci., North Carolina Univ., Charlotte, NC
fDate :
Oct. 31 2006-Nov. 2 2006
Abstract :
In this paper, we have developed a novel visualization framework to enable more effective visual analysis of large-scale news videos, where keyframes and keywords are automatically extracted from news video clips and visually represented according to their interestingness measurement to help audiences rind news stories of interest at first glance. 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 of large-scale news videos. Our news video visualization system is very useful for security applications and for general audiences to quickly find news topics of interest from among many channels
Keywords :
data visualisation; video signal processing; intelligent news video analysis; interactive visualization; large-scale news video; security application; semantic video classification; video visualization system; Computational intelligence; Computer industry; Computer science; Databases; Decision making; Informatics; Information analysis; Investments; Large-scale systems; Visualization; 1.2.6 [Artificial Intelligence]: Learning¿Concept learning; 1.3.6 [Computer Graphics]: Methodology and Techniques¿Interaction Techniques; News Visualization; Semantic Video Classification;
Conference_Titel :
Visual Analytics Science And Technology, 2006 IEEE Symposium On
Conference_Location :
Baltimore, MD
Print_ISBN :
1-4244-0591-2
Electronic_ISBN :
1-4244-0592-0
DOI :
10.1109/VAST.2006.261433
