Proposal of an Information Compilation Method for Massive News Video Data Based on their Time-Series Semantic Structure

Recent increase of digital storage capacity has enabled the creation of large-scale on-line broadcast video archives. In order to make full use of the data in the archive, it is necessary to let a user easily grasp the availability of certain video data and their contents. Considering this problem, we have been investigating efficient and effective retrieval and reusing methodologies of archived video data. The archive used as a test-bed consists of more than 1,000 hours of news video obtained from a Japanese news program during the past six years. This paper first proposes a news topic tracking and structuring method. A structure called the `topic thread structure', is organized so that it should represent the temporal flow of news topics originating from a specified news story. The paper next introduces a browsing and editing interface that enables the user to browse through news stories along the topic thread structure, and also assists the compilation of selected news stories as a customized video summary or a documentary. The method was applied to the archived news video data in order to observe the quality of the topic thread structure and the usability of the prototype interface. As a result, some structures represented the flow of topics quite close to real-world comprehension. In addition, experiments showed that when the structure could be considered meaningful, the interface combined with the structure could drastically reduce the time needed to browse through the archive for news stories related to the user's interest.