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A signature-based bag of visual words method for image indexing and search

机译:基于签名的视觉词袋图像索引与搜索方法

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In this paper, we revisit SDLC, an image retrieval method that adopts a signature-based approach to identify visual words, instead of the more conventional approach that identifies them by using clustering techniques. We start by providing a formal and generalized definition of the approach adopted in SDLC, which we call Signature-Based Bag of Visual Words. After that, we present a detailed study of SDLC parameters and experiments with distinct weighting schemes used to compute the ranking of results, comparing the method to well-known cluster-based bag of visual words approaches. When compared to the initial proposal of SDLC, the choice of different parameters and a new weighting scheme allowed us to considerably reduce the size of the textual representation generated by the method, reducing also the indexing times and the query processing times in all collections adopted in the experiments. Further, the SDLC outperforms the baselines in most of these collections. (C) 2015 Elsevier B.V. All rights reserved.
机译:在本文中,我们将重新探讨SDLC,它是一种基于签名的方法来识别视觉单词的图像检索方法,而不是使用聚类技术来识别视觉单词的更传统的方法。我们首先提供SDLC中采用的方法的正式定义,我们将其称为基于签名的视觉单词袋。之后,我们将对SDLC参数进行详细研究,并使用用于计算结果排名的不同加权方案进行实验,并将该方法与著名的基于聚类的视觉词袋方法进行比较。与SDLC的最初建议相比,不同参数的选择和新的加权方案使我们能够大大减少该方法生成的文本表示的大小,同时也减少了采用的所有集合中的索引编制时间和查询处理时间。实验。此外,SDLC在大多数此类馆藏中的表现均优于基线。 (C)2015 Elsevier B.V.保留所有权利。

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