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Video shot segmentation and key frame extraction based on SIFT feature

机译:基于SIFT特征的视频镜头分割和关键帧提取

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Content complexity can be defined by SIFT feature of video content. According to the differences in the content complexity and the content change ratio calculated from video content, a video shot boundary can be detected. In general, for programs with many storylines, every story takes place by turns so that the number of key frames in a story can be estimated with the method as stated above. At last, based on the video content complexity, as well as the difference between frames and the number of key frames, every key frame can be extracted from a video. The experimental results show that the proposed method can improve both the ratio of accuracy and recall in the stages of shot segmentation and key frame extraction, by using both the features of the content complexity and the content change ratio based on SIFT feature.
机译:内容复杂度可以通过视频内容的SIFT功能定义。根据根据视频内容计算出的内容复杂度和内容变化率的差异,可以检测视频镜头边界。通常,对于具有许多故事情节的程序,每个故事轮流发生,以便可以使用上述方法估算故事中关键帧的数量。最后,根据视频内容的复杂性以及帧和关键帧数之间的差异,可以从视频中提取每个关键帧。实验结果表明,该方法利用了内容复杂度的特征和基于SIFT特征的内容变化率,可以提高镜头分割和关键帧提取阶段的准确率和查全率。

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