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Videofall - A hierarchical search engine for VBS2022

Nguyen, Thao-Nhu, Puangthamawathanakun, Bunyarit, Healy, Graham orcid logoORCID: 0000-0001-6429-6339, Nguyen, Binh T., Gurrin, Cathal orcid logoORCID: 0000-0003-2903-3968 and Caputo, Annalina orcid logoORCID: 0000-0002-7144-8545 (2022) Videofall - A hierarchical search engine for VBS2022. In: 28th International Conference on MultiMedia Modeling, 6-10 June 2022, Phu Quoc, Vietnam. ISBN 978-3-030-98354-3

In this paper, we introduce a multi-user hierarchical video search tool called VIDEOFALL. Our objective, in the Video Browser Showdown (VBS) 2022, is to explore if VIDEOFALL interactive video retrieval under time constraints is a useful approach to take, given the overhead of requiring multiple users. It is our conjecture that combining the different skills of normal users can support a master user to retrieve target videos efficiently. The system is designed on top of the CLIP pre-trained model and the video keyframes are embedded into a vector space in which queries would also be encoded to facilitate retrieval.
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:video search; Video Browser Showdown; Interactive Video Retrieval; Hierarchical Engine; Multi-user Search Engine
Subjects:Computer Science > Information retrieval
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > INSIGHT Centre for Data Analytics
Research Institutes and Centres > ADAPT
Published in: MultiMedia Modeling. MMM 2021, Proceedings. Lecture Notes in Computer Science (LNCS) 13142. Springer, Cham. ISBN 978-3-030-98354-3
Publisher:Springer, Cham
Official URL:https://dx.doi.org/10.1007/978-3-030-98355-0_48
Copyright Information:© 2022 Springer
Funders:Science Foundation Ireland under Grant Agreement No. 18/CRT/6223, and 13/RC/2106_P2 at the ADAPT SFI Research Centre at DCU, ADAPT, the SFI Research Centre for AI-Driven Digital Content Technology, is funded by Science Foundation Ireland through the SFI Research Centres Programme.
ID Code:27036
Deposited On:20 Apr 2022 11:51 by Thao-Nhu Nguyen . Last Modified 03 Mar 2023 12:52

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