ADAMpro: Database Support for Big Multimedia Retrieval

Giangreco, Ivan and Schuldt, Heiko. (2016) ADAMpro: Database Support for Big Multimedia Retrieval. Datenbank-Spektrum, 16 (1). pp. 17-26.

[img] PDF - Accepted Version

Official URL: http://edoc.unibas.ch/51980/

Downloads: Statistics Overview


For supporting retrieval tasks within large multimedia collections, not only the sheer size of data but also the complexity of data and their associated metadata pose a challenge. Applications that have to deal with big multimedia collections need to manage the volume of data and to effectively and efficiently search within these data. When providing similarity search, a multimedia retrieval system has to consider the actual multimedia content, the corresponding structured metadata (e.g., content author, creation date, etc.) and—for providing similarity queries—the extracted low-level features stored as densely populated high-dimensional feature vectors. In this paper, we present ADAM pro , a combined database and information retrieval system that is particularly tailored to big multimedia collections. ADAM pro follows a modular architecture for storing structured metadata, as well as the extracted feature vectors and it provides various index structures, i.e., Locality-Sensitive Hashing, Spectral Hashing, and the VA-File, for a fast retrieval in the context of a similarity search. Since similarity queries are often long-running, ADAM pro supports progressive queries that provide the user with streaming result lists by returning (possibly imprecise) results as soon as they become available. We provide the results of an evaluation of ADAM pro on the basis of several collection sizes up to 50 million entries and feature vectors with different numbers of dimensions.
Faculties and Departments:05 Faculty of Science > Departement Mathematik und Informatik > Informatik > Databases and Information Systems (Schuldt)
UniBasel Contributors:Schuldt, Heiko and Giangreco, Ivan
Item Type:Article, refereed
Article Subtype:Research Article
Note:Publication type according to Uni Basel Research Database: Journal article -- The final publication is available at Springer, see Doi link
Identification Number:
edoc DOI:
Last Modified:04 May 2018 13:25
Deposited On:10 Oct 2017 09:38

Repository Staff Only: item control page