Video Retrieval Method Using Sparse Bayesian Modeling

ZHU Li

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Video Retrieval Method Using Sparse Bayesian Modeling

更新时间：2023-12-11

- Video Retrieval Method Using Sparse Bayesian Modeling
- Acta Scientiarum Naturalium Universitatis SunYatseni Vol. 51, Issue 5, Pages: 36-39(2012)
- 作者机构：
  
  广东技术师范学院工业实训中心,广东,广州,510665
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2012，
  
  Published Online：25 September 2012，
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ZHU Li. Video Retrieval Method Using Sparse Bayesian Modeling. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 51(5):36-39(2012)
DOI：

ZHU Li. Video Retrieval Method Using Sparse Bayesian Modeling. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 51(5):36-39(2012) DOI：

摘要

结合压缩感知的稀疏表示理论和贝叶斯模型，提出一种在数据库中进行快速有效的视频信息查询和视频恢复的方法。根据最小l

范数重构数据信息的要求，方法利用贝叶斯模型对参数进行估计，并通过稀疏特性对视频分类和特征提取，达到恢复视频信息的目的。实验结果表明，比较主成成份分析和随机投影算法，该文的实现方法具有更好的恢复性能。

Abstract

Combining Compressed Sensing sparse theory with Bayesian modeling

a faster and more effective method of video information retrieval is proposed in database. Based on minimizing

principle for classification and feature extraction

the method implements video retrieval requirement by utilizing Bayesian modeling to automatically estimate the regularization parameters. Experimental results demonstrate that the proposed method performs better retrieval performances than PCA and RP algorithm.

关键词

稀疏贝叶斯模型压缩感知视频恢复

Keywords

sparseBayesian modelingcompressed sensingvideo retrieval

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Related Institution

College of Electronic and Information Engineering,Foshan University

School of Electronic and Information,Guangdong Polytechnic Normal University,Guangzhou

Department of Computer, Foshan University, Foshan

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佛山科学技术学院计算机系，广东佛山 528000

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