Alam, Naushad, Graham, Yvette and Gurrin, Cathal ORCID: 0000-0003-2903-3968 (2021) Memento: a prototype lifelog search engine for LSC’21. In: The fourth Lifelog Search Challenge (LSC 21), 19th Nov 2021, Taipei, Taiwan (Online). ISBN 978-1-4503-8533-6
Abstract
In this paper, we introduce a new lifelog retrieval system called
Memento that leverages semantic representations of images and
textual queries projected into a common latent space to facilitate
effective retrieval. It bridges the semantic gap between complex visual scenes/events and user information needs expressed as textual
and faceted queries. The system, developed for the 2021 Lifelog
Search Challenge also has a minimalist user interface that includes
primary search, temporal search, and visual data filtering components.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Workshop |
Refereed: | Yes |
Uncontrolled Keywords: | semantic image representation |
Subjects: | Computer Science > Information retrieval Computer Science > Lifelog |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Initiatives and Centres > INSIGHT Centre for Data Analytics |
Published in: | LSC '21: Proceedings of the 4th Annual on Lifelog Search Challenge. . Association for Computing Machinery (ACM). ISBN 978-1-4503-8533-6 |
Publisher: | Association for Computing Machinery (ACM) |
Official URL: | https://doi.org/10.1145/3463948.3469069 |
Copyright Information: | ©2021 The Authors. Open access (CC-BY-4.0) |
Funders: | y Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289_P2, co-funded by the European Regional Development Fund. |
ID Code: | 26463 |
Deposited On: | 15 Nov 2021 12:45 by Naushad Alam . Last Modified 15 Dec 2021 15:32 |
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