There are various TV programs such as travel and educational programs. While watching TV programs, viewers often search related information about the programs through the Web. Nevertheless, as TV programs keep playing, viewers possibly miss some important scenes when searching the Web. As a result, their enjoyment would be spoiled. Another problem is that there are various topics in each scene of a video, and viewers usually have different levels of knowledge. Thus, it is important to detect topics in videos and supplement videos with related information automatically. In this paper, the authors propose a novel automatic video reinforcing system with two functions: 1 a media synchronization mechanism, which presents supplementary information synchronized with videos, in order to enable viewers to effectively understand the geographic data in videos; 2 a video reconstruction mechanism, which generates new video contents based on viewers' interests and knowledge by adding and removing scenes, in order to enable viewers to enjoy the generated videos without additional search.
['Yuanyuan Wang', 'Daisuke Kitayama', 'Yukiko Kawai', 'Kazutoshi Sumiya', 'Yoshiharu Ishikawa']
An Automatic Video Reinforcing System for TV Programs using Semantic Metadata from Closed Captions