Gasser, Ralph and Rossetto, Luca and Heller, Silvan and Schuldt, Heiko. (2020) Cottontail DB: An Open Source Database System for Multimedia Retrieval and Analysis. In: Proceedings of 28th ACM International Conference on Multimedia (MM 2020). New York, pp. 4465-4468.
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Official URL: https://edoc.unibas.ch/81639/
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Abstract
Multimedia retrieval and analysis are two important areas in "Big data" research. They have in common that they work with feature vectors as proxies for the media objects themselves. Together with metadata such as textual descriptions or numbers, these vectors describe a media object in its entirety, and must therefore be considered jointly for both storage and retrieval. In this paper we introduce Cottontail DB, an open source database management system that integrates support for scalar and vector attributes in a unified data and query model that allows for both Boolean retrieval and nearest neighbour search. We demonstrate that Cottontail DB scales well to large collection sizes and vector dimensions and provide insights into how it proved to be a valuable tool in various use cases ranging from the analysis of MRI data to realizing retrieval solutions in the cultural heritage domain.
Faculties and Departments: | 05 Faculty of Science > Departement Mathematik und Informatik > Informatik > Databases and Information Systems (Schuldt) |
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UniBasel Contributors: | Schuldt, Heiko and Heller, Silvan and Gasser, Ralph |
Item Type: | Conference or Workshop Item, refereed |
Conference or workshop item Subtype: | Conference Paper |
Publisher: | Association for Computing Machinery |
e-ISBN: | 978-1-4503-7988-5 |
Note: | Publication type according to Uni Basel Research Database: Conference paper |
Language: | English |
Identification Number: | |
edoc DOI: | |
Last Modified: | 07 Jun 2022 15:43 |
Deposited On: | 02 Feb 2021 13:12 |
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