Topic-based inter-video structuring of a large-scale news video corpus

We propose a topic-based inter-video news video corpus structuring method and a visual interface to efficiently browse through the structured corpus. Such inter-video structuring was not deeply sought in previous works. The topic-based structure is analyzed by closed-caption text analysis; topic segmentation and tracking. The visual interface provides the ability to 1) search and select a topic by query terms and 2) track a topic thread interactively referring to the text analysis results. Although topic retrieval is somewhat similar to conventional video retrieval methods, the combination with topic tracking makes it remarkably easy to narrow down the results that match a user's interest and moreover reveal underlying content-based structures, where the structure itself contains rich information.