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Automatic Scene Detection in News Program by Integrating Visual Feature and Rules
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Automatic Scene Detection in News Program by Integrating Visual Feature and Rules
Xingquan Zhu7 , Lide Wu8 , Xiangyang Xue8 , Xiaoye Lu8 and Jianping Fan9 
| (7) |
Department of Computer Science, Purdue University, W. Lafayette, IN 47907, USA |
| (8) |
Department of Computer Science, Fudan University, Shanghai, 200433, China |
| (9) |
Department of Computer Science, University of North Carolina at Charlotte, USA |
Abstract
Organizing video sequences from shot level to scene level is a challenging task, however, without the scene information, it
will be very hard to extract the content of the video. In this paper, a visual and rule information integrated strategy is
proposed to detect the scene information of the News programs. First, we extract out the video caption and anchor person (AP) shots in the video. Second, the rules among the scene, video caption, AP shots will be used to detect the scenes. Third, the visual features will also be used to analysis the scene information in
the region which can not be covered by the rules. And experimental results based on this strategy are provided and analyzed
on broadcast News videos.
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