Efficient and Language Independent News Story Segmentation for Telecast News Videos

A TV news program comprises a continuous video stream containing a number of news stories, interspersed with commercials and headlines. This paper presents a method to detect the story boundaries and to separate out the stories from the other components and from each other. The method is based on movement of ticker text bands and repetition of ticker texts during different parts of a news program. The method does not use any language processing tool and is independent of language of telecast. It uses some simple features to distinguish news from the advertisements and can be used for large scale news indexing. We produce some test results on channels telecasting in English and few other Indian languages.