LireSolr - A Visual Information Retrieval Server

被引：1

作者：

Lux, Mathias ^{[1
]}

Riegler, Michael ^{[2
]}

Halvorsen, Pal ^{[2
]}

MacStravic, Glenn ^{[3
]}

机构：

[1] Klagenfurt Univ, Univ Str 65-67, Klagenfurt, Austria

[2] Simula Res Lab, Martin Linges V 17-25, Oslo, Norway

[3] World Intellectual Property Org, 34 Chemin Colombettes, Geneva, Switzerland

来源：

PROCEEDINGS OF THE 2017 ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA RETRIEVAL (ICMR'17) | 2017年

关键词：

Visual information retrieval;

D O I：

10.1145/3078971.3079014

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we present LireSolr, an open source image retrieval server, build on top of the LIRE library and the Apache Solr search server. With LireSolr, visual information retrieval can be run on a server, which allows better distribution of workloads and simplifies applications in several areas including mobile and web. Furthermore, we showcase several example scenarios how LireSolr can be used to point out the broad range of possibilities and applications. The system is easy to install and setup, and the large number of retrieval tools either provided by LIRE or by other Apache Solr is made easily available on the search server. Moreover, our tool demonstrates how predictions from CNNs can easily be used to extend the visual information retrieval functionality.

引用

页码：466 / 469

页数：4

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