Storing Feature Vectors in Relational Image Data Warehouses

被引：0

作者：

Rocha, Guilherme Muzzi ^{[1
]}

Capelo, Piero Lima ^{[1
]}

Carniel, Anderson Chaves ^{[2
]}

Aguiar, Cristina Dutra ^{[1
]}

机构：

[1] Univ Sao Paulo, Dept Comp Sci, Sao Paulo, Brazil

[2] Univ Fed Sao Carlos, Dept Comp Sci, Sao Carlos, Brazil

来源：

NEW TRENDS IN DATABASE AND INFORMATION SYSTEMS, ADBIS 2022 | 2022年 / 1652卷

基金：

巴西圣保罗研究基金会;

关键词：

Data warehouse design; Image data; Analytical queries;

D O I：

10.1007/978-3-031-15743-1_30

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

An image data warehousing also manipulates image data represented by feature vectors and attributes for similarity search. In this paper, we study the impact of storing feature vectors on the performance of analytical queries extended with a similarity search predicate over images. We consider the management of huge data volumes. Thus, we use Spark as support. Experimental results showed that depending on the query characteristics and the data warehouse design, the difference in performance was up to 86.23%. Based on these results, we propose guidelines for storing feature vectors in relational image data warehouses.

引用

页码：323 / 331

页数：9

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