Transactional Support for Visual Instance Search

被引：1

作者：

Lejsek, Herwig ^{[1
]}

Asmundsson, Fridrik Heidar ^{[1
]}

Jonsson, Bjorn Thor ^{[2
,3
]}

Amsaleg, Laurent ^{[4
]}

机构：

[1] Videntifier Technol, Reykjavik, Iceland

[2] Reykjavik Univ, Reykjavik, Iceland

[3] IT Univ Copenhagen, Copenhagen, Denmark

[4] CNRS IRISA, Rennes, France

来源：

SIMILARITY SEARCH AND APPLICATIONS, SISAP 2018 | 2018年 / 11223卷

关键词：

NEAREST; QUANTIZATION;

D O I：

10.1007/978-3-030-02224-2_6

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This article addresses the issue of dynamicity and durability for scalable indexing of very large and rapidly growing collections of local features for visual instance retrieval. By extending the NV-tree, a scalable disk-based high-dimensional index, we show how to implement the ACID properties of transactions which ensure both dynamicity and durability. We present a detailed performance evaluation of the transactional NV-tree, showing that the insertion throughput is excellent despite the effort to enforce the ACID properties.

引用

页码：73 / 86

页数：14

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