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基于潜在主题的分布式视觉检索模型 被引量：1

Distributed Visual Retrieval Model Based on Potential Theme
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摘要 为将文档聚类划分的分布式检索方法直接应用于视觉检索领域,提出一种基于潜在主题的分布式视觉检索模型。给出模型框架,包括图像视觉单词的数据集划分方法和图像子集选择方法,以此优化图像分布式检索性能。实验结果表明,该模型在不降低检索准确率的前提下,能优先选择少量的图像子集进行检索,并提高查询的吞吐量。 In order to use distributed retrieval method for document clustering partition directly in visual search field,this paper proposes a distributed visual retrieval model based on potential theme.This paper gives the model framework,including dataset partition method of image visual words and image subset selection method,to optimize image distributed retrieval performance.Experimental results show that this model searches in a few selected image collections without losing retrieval accuracy and improves the query throughput.
作者 陈宜明 段凌宇 黄艳 李冰 林杰 黄铁军
机构地区 北京大学信息科学技术学院 中国科学院沈阳计算技术研究所 中国科学院研究生院
出处 《计算机工程》 CAS CSCD 2012年第24期146-151,共6页 Computer Engineering
基金 国家自然科学基金资助项目(60902057) 国家"973"计划基金资助项目(2009CB320902)
关键词 分布式检索 视觉检索 词袋模型 图像数据集划分 图像数据集选择 潜在主题 distributed retrieval visual retrieval Bag of Word（BoW） model image dataset division image dataset selection potential theme
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
  • 相关文献

参考文献11

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二级参考文献15

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共引文献10

同被引文献16

引证文献1

二级引证文献15

计算机工程
2012年 第24期

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