Cross-Lingual Retrieval of Identical News Events by Near-Duplicate Video Segment Detection

نویسندگان

  • Akira Ogawa
  • Tomokazu Takahashi
  • Ichiro Ide
  • Hiroshi Murase
چکیده

Recently, for reusing large quantities of accumulated news video, technology for news topic searching and tracking has become necessary. Moreover, since we need to understand a certain topic from various viewpoints, we focus on identical event detection in various news programs from different countries. Currently, text information is generally used to retrieve news video. However, cross-lingual retrieval is complicated by machine translation performance and different viewpoints and cultures. In this paper, we propose a cross-lingual retrieval method for detecting identical news events that exploits image information together with text information. In an experiment, we verified the effectiveness of making use of the existence of near-duplicate video segments and the possibility of improving retrieval performance.

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تاریخ انتشار 2008