Duygulu, PınarPan J.-Y.Forsyth, D.A.2016-02-082016-02-082004http://hdl.handle.net/11693/27423Date of Conference: October 10 - 16, 2004News 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.EnglishAuto-documentaryDuplicate sequencesGraph-based multi-modal topic discoveryMatching logosNews video analysisAlgorithmsComputer visionDatabase systemsGraphic methodsInformation analysisMathematical modelsMultimedia systemsInformation retrieval systemsConference Paper10.1145/1027527.1027719