计算机应用 ›› 2011, Vol. 31 ›› Issue (02): 358-361.

• 图形图像处理 • 上一篇    下一篇

基于粒子群的关键帧提取算法

张建明1,蒋兴杰2,李广翠3,姜靓3   

  1. 1. 江苏大学计算机科学与通信工程学院
    2. 江苏大学
    3.
  • 收稿日期:2010-07-20 修回日期:2010-09-11 发布日期:2011-02-01 出版日期:2011-02-01
  • 通讯作者: 蒋兴杰
  • 基金资助:
    江苏省自然科学基金;国家自然科学基金资助项目

Key frame extraction based on particle swarm optimization

  • Received:2010-07-20 Revised:2010-09-11 Online:2011-02-01 Published:2011-02-01

摘要: 关键帧提取是基于内容的视频检索中的重要一步,为了能够有效地提取出不同类型视频的关键帧,提出一种基于粒子群的关键帧提取算法。该方法首先提取出视频中每帧的全局运动和局部运动特征,然后通过粒子群算法自适应地提取视频关键帧。实验结果表明,采用该算法对不同类型的视频提取出的关键帧具有较好的代表性。

关键词: 视频检索, 关键帧提取, 粒子群, 运动特征

Abstract: Key frame extraction was an important step in video retrieval. In order to effectively extract key frames of different video types, a key frame extraction algorithm based on particle swarm was proposed in this paper. This method first extracted the global motion and local motion features in each frame, and video key frame was extracted by Particle Swarm Optimization (PSO) adaptively. The experimental results show that the key frame extraction algorithm for different types of video is more representative.

Key words: video retrieval, key frame extraction, Particle Swarm Optimization (PSO), motion characteristic