Towards auto-documentary: Tracking the evolution of news stories
Please cite this item using this persistent URLhttp://hdl.handle.net/11693/27423
ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia
- Conference Paper 
News videos constitute an important source of information for tracking and documenting important events. In these videos, news stories are often accompanied by short video shots that tend to be repeated during the course of the event. Automatic detection of such repetitions is essential for creating auto-documentaries, for alleviating the limitation of traditional textual topic detection methods. In this paper, we propose novel methods for detecting and tracking the evolution of news over time. The proposed method exploits both visual cues and textual information to summarize evolving news stories. Experiments are carried on the TREC-VID data set consisting of 120 hours of news videos from two different channels.