Total recall II: Query expansion revisited

Ondřej Chum, Andrej Mikulík, Michal Perdoch, Jiri Matas
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引用次数: 310

Abstract

Most effective particular object and image retrieval approaches are based on the bag-of-words (BoW) model. All state-of-the-art retrieval results have been achieved by methods that include a query expansion that brings a significant boost in performance. We introduce three extensions to automatic query expansion: (i) a method capable of preventing tf-idf failure caused by the presence of sets of correlated features (confusers), (ii) an improved spatial verification and re-ranking step that incrementally builds a statistical model of the query object and (iii) we learn relevant spatial context to boost retrieval performance. The three improvements of query expansion were evaluated on standard Paris and Oxford datasets according to a standard protocol, and state-of-the-art results were achieved.
总召回II:重新访问查询展开
最有效的特定对象和图像检索方法是基于词袋(BoW)模型。所有最先进的检索结果都是通过包含查询扩展的方法实现的,这大大提高了性能。我们为自动查询扩展引入了三种扩展:(i)一种能够防止由于相关特征集(混淆者)的存在而导致的tf-idf失败的方法,(ii)一种改进的空间验证和重新排序步骤,该步骤逐步构建查询对象的统计模型,以及(iii)我们学习相关的空间上下文以提高检索性能。根据标准协议在标准Paris和Oxford数据集上对查询扩展的三种改进进行了评估,获得了最先进的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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