Nguyen, Thao-Nhu, Puangthamawathanakun, Bunyarit, Healy, Graham 
ORCID: 0000-0001-6429-6339, Nguyen, Binh T., Gurrin, Cathal ORCID: 0000-0003-2903-3968 and Caputo, Annalina ORCID: 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
Abstract
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.
Metadata
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Event Type: | Conference |
| Refereed: | Yes |
| 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 |
Documents
Full text available as:
Preview |
PDF
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
1MB |
Downloads
Downloads
Downloads per month over past year
Archive Staff Only: edit this record