Contextual Query Expansion for Image Retrieval

Contextual Query Expansion for Image Retrieval
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用于图像检索的上下文查询扩展

DOI:
10.1109/tmm.2014.2305909
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发表时间:
2014-06
期刊:
IEEE Trans. on Multimedia
影响因子:
--
通讯作者:
Li Jintao
Li Jintao
中科院分区:
其他
文献类型:
--
作者:
Zhang Yongdong;Tan Jianlong;Guo Li;Li Jintao

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在本文中,我们研究了图像检索的问题,通过引入上下文查询扩展,以解决基于词袋的框架的缺点:视觉词量化的语义差距,以及由于查询扩展的效率和存储损失。我们的方法是建立在共同的视觉模式(CVP),这是两个图像之间的独特的视觉结构,并具有丰富的上下文信息。基于CVP,分别研究了视觉词级和图像级的上下文查询扩展。对于视觉词级的扩展,我们发现上下文同义视觉词(CSVW)和扩展一个词在查询图像与其CSVW,以提高检索的准确性。CSVW是出现在相同CVP中并且具有相同上下文含义的词,即相似的空间布局和几何变换。对于图像级扩展,具有相同CVP的数据库图像由链表组织,并且具有与查询图像相同的CVP但未包括在结果中的图像被自动扩展。这两个展开的主要计算是离线进行的,它们可以集成到倒排文件中,并有效地应用于数据集中的所有图像。在三个参考数据集和一百万幅图像的数据集上进行的实验证明了该方法的有效性和效率。
In this paper, we study the problem of image retrieval by introducing contextual query expansion to address the shortcomings of bag-of-words based frameworks: semantic gap of visual word quantization, and the efficiency and storage loss due to query expansion. Our method is built on common visual patterns (CVPs), which are the distinctive visual structures between two images and have rich contextual information. With CVPs, two contextual query expansions on visual word-level and image-level are explored, respectively. For visual word-level expansion, we find contextual synonymous visual words (CSVWs) and expand a word in the query image with its CSVWs to boost retrieval accuracy. CSVWs are the words that appear in the same CVPs and have same contextual meaning, i.e. similar spatial layout and geometric transformations. For image-level expansion, the database images that have the same CVPs are organized by linked list and the images that have the same CVPs as the query image, but not included in the results are automatically expanded. The main computation of these two expansions is carried out offline, and they can be integrated into the inverted file and efficiently applied to all images in the dataset. Experiments conducted on three reference datasets and a dataset of one million images demonstrate the effectiveness and efficiency of our method.
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