结合Tsallis熵与Jensen距离的视频关键帧抽取方法

doi:10.3969/j.issn.1000-3428.2016.02.049

计算机工程

结合Tsallis熵与Jensen距离的视频关键帧抽取方法

李梁凯,徐庆,罗小小

(天津大学计算机科学与技术学院,天津 300072)

收稿日期:2015-01-22 出版日期:2016-02-15 发布日期:2016-01-29
作者简介:李梁凯(1991-),男,硕士研究生,主研方向为多媒体技术、图像处理;徐庆,教授;罗小小,硕士研究生。
基金项目:
国家自然科学基金资助项目(61471261,61179067,U1333110)。

Video Key Frame Extraction Method Combined with Tsallis Entropy and Jensen Distance

LI Liangkai,XU Qing,LUO Xiaoxiao

(School of Computer Science and Technology,Tianjin University,Tianjin 300072,China)

Received:2015-01-22 Online:2016-02-15 Published:2016-01-29

摘要/Abstract

摘要： 为快速有效地表征视频内容,提出一种视频关键帧抽取方法。结合Tsallis熵和Jensen距离计算相邻视频帧间差距,将视频分割为镜头,并根据镜头内视觉内容变化的多少将其分割为子镜头,最终抽取关键帧。同时提出视频帧间的距离度量标准,用于自适应地选取最优Tsallis 熵指数。实验测试结果表明,该方法简单高效,对物体运体有较好的鉴别能力。

关键词: 关键帧抽取, Jensen-Tsallis距离, 信息熵, 熵指数, 镜头分割

Abstract: In order to summarize the main content of a video sequence quickly and effectively,this paper proposes a new method for extracting video key frames.The proposed technique makes use of Jensen-Tsallis distance to estimate the frame-by-frame distance between consecutive video images,to segment a video into shot,and into subshot either with or without large change of the video content.Video key frames are selected based on the subshot.It also proposes a measure for the difference between video frames to adaptively set an optimal index used for Tsallis entropy.Experimental result shows that the novel method is simple yet effective,and has better ability to identify the moving objects.

Key words: key frame extraction, Jensen-Tsallis distance, information entropy, entropy index, shot segmentation

中图分类号:

TP18

李梁凯,徐庆,罗小小. 结合Tsallis熵与Jensen距离的视频关键帧抽取方法[J]. 计算机工程, doi: 10.3969/j.issn.1000-3428.2016.02.049.

LI Liangkai,XU Qing,LUO Xiaoxiao. Video Key Frame Extraction Method Combined with Tsallis Entropy and Jensen Distance [J]. Computer Engineering, doi: 10.3969/j.issn.1000-3428.2016.02.049.

参考文献

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结合Tsallis熵与Jensen距离的视频关键帧抽取方法

Video Key Frame Extraction Method Combined with Tsallis Entropy and Jensen Distance

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