Tran, Ly-Duyen, Nguyen, Manh-Duy, Dang-Nguyen, Duc-Tien, Heller, Silvan, Spiess, Florian, Lokoč, Jakub, Peška, Ladislav, Nguyen, Thao-Nhu, Khan, Omar Shahbaz, Duane, Aaron, Jónsson, Björn þór, Rossetto, Luca, Yen, An-Zi, Alateeq, Ahmed, Alam, Naushad, Tran, Minh-Triet, Healy, Graham, Schoeffmann, Klaus and Gurrin, Cathal ORCID: 0000-0003-4395-7702 (2023) Comparing Interactive Retrieval Approaches at the Lifelog Search Challenge 2021. IEEE Access, 11 . pp. 30982-30995. ISSN 2169-3536
Abstract
The Lifelog Search Challenge (LSC) is an interactive benchmarking evaluation workshop
for lifelog retrieval systems. The challenge was first organised in 2018 aiming to find the system that can
quickly retrieve relevant lifelog images for a given semantic query. This paper provides an analysis of the performance of all 17 systems participating in the 4th LSC workshop held at the 2021 Annual ACM International Conference on Multimedia Retrieval (ICMR). LSC’21 was the largest effort at comparing different approaches to interactive lifelog retrieval systems seen thus far. Findings from the challenge suggest that many different interactive factors contribute to the success (or otherwise) of participating teams. In this paper, we provide an overview of the LSC’21 challenge, introduce each team’s approach and explore these factors in depth and offer clues on how to develop a high-performing interactive lifelog search engine
Metadata
Item Type: | Article (Published) |
---|---|
Refereed: | Yes |
Uncontrolled Keywords: | Interactive systems; Multimodal sensors; Visualization; Cameras; Information retrieval; Benchmark testing; Lifelog; information retrieval; multimodal; analytics |
Subjects: | Computer Science > Computer software Computer Science > Interactive computer systems Computer Science > Multimedia systems Computer Science > Information storage and retrieval systems Computer Science > Lifelog |
DCU Faculties and Centres: | UNSPECIFIED |
Publisher: | Institute of Electrical and Electronics Engineers |
Official URL: | https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumb... |
Copyright Information: | Authors |
Funders: | Science Foundation Ireland Centre for Research Training, Insight Science Foundation Ireland (SFI) Research Centre for Data Analytics, Czech Science Foundation (GAČR), ADAPT—Centre for Digital Content Technology, Swiss National Science Foundation, Charles University |
ID Code: | 29962 |
Deposited On: | 29 Apr 2024 14:24 by Ly Duyen Tran . Last Modified 29 Apr 2024 14:24 |
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