Abstract
Exquisitor is a scalable media exploration system based on interactive learning. To satisfy a user's information need, the system asks the user for feedback on media items and uses that feedback to interactively construct a classifier, that is in turn used to identify the next potentially relevant set of media items. To facilitate effective exploration of a collection, the system offers filters to narrow the scope of exploration, search functionality for finding good examples for the classifier, and support for timeline browsing of videos or image sequences. For this year's Lifelog Search Challenge, we have enhanced Exquisitor to better support tasks with a temporal component, by adding features that allow the user to build multiple classifiers and merge the classifier results, using both traditional set operators and advanced temporal operators.
Original language | English |
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Title of host publication | LSC '21: Proceedings of the 4th Annual on Lifelog Search Challenge |
Number of pages | 4 |
Place of Publication | Taipei, Taiwan (virtual) |
Publisher | Association for Computing Machinery |
Publication date | Aug 2021 |
Pages | 3-6 |
DOIs | |
Publication status | Published - Aug 2021 |
Keywords
- Scalable media exploration
- Interactive learning
- User feedback
- Media classification
- Temporal operators