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SVM Based Shot Boundary Detection Using Block Motion Feature Based on Statistical Moments

机译:基于SVM的射击边界检测使用基于统计时刻的块运动特征

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Temporal video segmentation is of fundamental importance in order to facilitate user’s access to huge volume of video data as well as for video summarization.The objective of shot boundary detection is to partition the video into meaningful, basic structural units called shots. In this paper, a shot boundary detection technique has been proposed for cuts. The method extracts block feature based similarities from the frames of the input video. Statistical moments up to second order are used to measure the motion present in the frames. Feature vectors are generated using a sliding window over time and are trained by a SVM to identify the cuts.
机译:时间视频分割是重要的重要性,以便于用户访问大量的视频数据以及视频摘要。拍摄边界检测的目标是将视频分区为有意义的基本结构单元,称为射击。本文提出了一种用于切割的射门边界检测技术。该方法从输入视频的帧中提取基于块特征的相似性。统计时刻最多可用于测量框架中存在的运动。使用滑动窗口产生特征向量,随着时间的推移,由SVM训练以识别切割。

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