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MemoriEase: an interactive lifelog retrieval system for LSC’23

Tran, Quang-Linh orcid logoORCID: 0000-0002-5409-0916, Tran, Ly-Duyen orcid logoORCID: 0000-0002-9597-1832, Nguyen, Binh T. and Gurrin, Cathal orcid logoORCID: 0000-0003-2903-3968 (2023) MemoriEase: an interactive lifelog retrieval system for LSC’23. In: 6th Annual ACM Lifelog Search Challenge (LSC '23), 12-15 June 2023, Thessaloniki, Greece. ISBN 979-8-4007-0188-7

Lifelogging is an activity of recording all events that happen in the daily life of an individual. The events can contain images, audio, health index, etc which are collected through various devices such as wearable cameras, smartwatches, and other digital services. Exploiting lifelog data can bring significant benefits for lifeloggers from creating personalized healthcare plans to retrieving events in the past. In recent years, there has been a growing development of interactive lifelog retrieval systems, such as competitors at the annual Lifelog Search Challenge (LSC), to assist lifeloggers in finding events from the past. This paper introduces an interactive lifelog image retrieval called MemoriEase for the LSC’23 challenge. This system combines concept-based and embedding-based retrieval approaches to answer accurate images for LSC’23 queries. This system uses BLIP for the embedding-based retrieval approach to reduce the semantic gap between images and text queries. The concept-based retrieval approach uses full-text search in Elasticsearch to retrieve images having visual concepts similar to keywords in the query. Regarding the user interface, we make it as simple as possible to make novices users can use it with only a small effort. This is the first version of MemoriEase and we expect this can help users perform well in the LSC’23 competition
Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Uncontrolled Keywords:lifelog; interactive retrieval system; unified vision-language representation
Subjects:Computer Science > Information retrieval
Computer Science > Multimedia systems
Computer Science > Information storage and retrieval systems
Computer Science > Lifelog
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > ADAPT
Published in: Gurrin, Cathal and Jónsson, Björn Þór, (eds.) LSC '23: Proceedings of the 6th Annual ACM Lifelog Search Challenge. . Association for Computer Machinery (ACM). ISBN 979-8-4007-0188-7
Publisher:Association for Computer Machinery (ACM)
Official URL:https://doi.org/10.1145/3592573.3593101
Copyright Information:© 2023 The Authors
Funders:Science Foundation Ireland at ADAPT, the SFI Research Centre for AI-Driven Digital Content Technology at Dublin City University [13/RC/2106_P2].
ID Code:28885
Deposited On:08 Aug 2023 13:18 by Linh Tran . Last Modified 08 Mar 2024 11:02

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