计算机科学 ›› 2014, Vol. 41 ›› Issue (8): 286-288.doi: 10.11896/j.issn.1002-137X.2014.08.060

• 图形图像与模式识别 • 上一篇    下一篇

基于内容代表性评价的关键帧抽取

顾益军,解易,夏天   

  1. 中国人民公安大学信息安全保卫学院 北京100872;中国人民公安大学信息安全保卫学院 北京100872;中国人民大学数据工程与知识工程教育部重点实验室 北京100872;中国人民大学信息资源管理学院 北京100872
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受公安部重点研究计划项目(2011ZDYJGADX016),北京高等学校青年英才计划项目(YETP1366)资助

Keyframe Extraction Based on Representative Evaluation of Contents

GU Yi-jun,XIE Yi and XIA Tian   

  • Online:2018-11-14 Published:2018-11-14

摘要: 视频关键帧提取技术是对视频进行摘要来提高视频内容访问效率的一种操作。传统的方法主要采用聚类的方法,未给出可信的关键帧代表性描述。尝试基于图计算算法实现关键帧抽取,该算法可以将一段视频中候选帧及其之间的关系表示成一个相关图,通过各帧间基于相关性对相邻帧的分值分配进行迭代计算,实现候选帧内容代表性评价;并提出了一种高效的帧间相关性计算方法。该方法通过两帧图像的最大稳定颜色区域(maximally stable colour region,MSCR)的匹配情况判定它们的相关性。在测试视频上将该算法与传统算法进行了对比测试,测试的结果验证了该算法的有效性。

关键词: 关键帧提取,相关性计算,视频

Abstract: The keyframe extraction is a visual summary method.It enhances the accessibility to the visual content.Traditional methods extract keyframes through clustering.These methods don’t provide reliable descriptions of keyframe representative.This paper proposed a novel keyframe extraction method through a graph model representing the candidate keyframes and the correlations between them.The representative of candidate keyframe was calculated through propagating grade between correlated candidate keyframes iteratively.To support the calculation of the representative,the paper introduced a correlation calculation method according to how well the maximally stable colour regions of two frames match to each other.The experiments were conducted on several test videos and the results validated our keyframe extraction method.

Key words: Keyframe extraction,Correlation calculation,Video

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