| 基于粒子群的关键帧提取算法 |
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| 引用本文： | 张建明,蒋兴杰,李广翠,姜靓.基于粒子群的关键帧提取算法[J].计算机应用,2011,31(2):358-361. |
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| 作者姓名： | 张建明 蒋兴杰 李广翠 姜靓 |
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| 作者单位： | 1. 江苏大学计算机科学与通信工程学院2. 江苏大学3. |
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| 基金项目： | 国家自然科学基金资助项目，江苏省自然科学基金资助项目 |
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| 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。
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| 关 键 词： | 视频检索 关键帧提取 粒子群 运动特征 |
| 收稿时间： | 2010-07-20 |
| 修稿时间： | 2010-09-11 |
Key frame extraction based on particle swarm optimization |
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| ZHANG Jian-ming,JIANG Xing-jie,LI Guang-cui,JIANG Liang.Key frame extraction based on particle swarm optimization[J].journal of Computer Applications,2011,31(2):358-361. |
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| Authors: | ZHANG Jian-ming JIANG Xing-jie LI Guang-cui JIANG Liang |
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| Affiliation: | (School of Computer Science and Telecommunication Engineering,Jiangsu University,Zhenjiang Jiangsu 212013,China) |
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| 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. |
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| Keywords: | video retrieval key frame extraction Particle Swarm Optimization (PSO) motion characteristic |
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