DocumentCode :
1505541
Title :
Tracking Web Video Topics: Discovery, Visualization, and Monitoring
Author :
Cao, Juan ; Ngo, Chong-Wah ; Zhang, Yong-dong ; Li, Jin-tao
Author_Institution :
Inst. of Comput. Technol., Beijing, China
Volume :
21
Issue :
12
fYear :
2011
Firstpage :
1835
Lastpage :
1846
Abstract :
Despite the massive growth of web-shared videos in Internet, efficient organization and monitoring of videos remains a practical challenge. While nowadays broadcasting channels are keen to monitor online events, identifying topics of interest from huge volume of user uploaded videos and giving recommendation to emerging topics are by no means easy. Specifically, such process involves discovering of new topic, visualization of the topic content, and incremental monitoring of topic evolution. This paper studies the problem from three aspects. First, given a large set of videos collected over months, an efficient algorithm based on salient trajectory extraction on a topic evolution link graph is proposed for topic discovery. Second, topic trajectory is visualized as a temporal graph in 2-D space, with one dimension as time and another as degree of hotness, for depicting the birth, growth, and decay of a topic. Finally, giving the previously discovered topics, an incremental monitoring algorithm is proposed to track newly uploaded videos, while discovering new topics and giving recommendation to potentially hot topics. We demonstrate the application on three months´ videos crawled from YouTube during December 2008 to February 2009. Both objective and user studies are conducted to verify the performance.
Keywords :
Internet; data visualisation; graph theory; information retrieval; video signal processing; Internet; Web video topic tracking; Web-shared videos; broadcasting channels; salient trajectory extraction; temporal graph; topic content visualization; topic discovery; topic evolution incremental monitoring; topic evolution link graph; topic trajectory; Algorithm design and analysis; Monitoring; Recommender systems; Trajectory; Visualization; Topic trajectory mining; video recommendation; visualization;
fLanguage :
English
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
1051-8215
Type :
jour
DOI :
10.1109/TCSVT.2011.2148470
Filename :
5756649
Link To Document :
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