| Autor: |
Anju Jose Tom, Laura Toni, Thomas Maugey |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
EURASIP Journal on Advances in Signal Processing, Vol 2023, Iss 1, Pp 1-16 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1687-6180 |
| DOI: |
10.1186/s13634-023-01069-0 |
| Popis: |
Abstract This work proposes an end-to-end user-centric sampling method aimed at selecting the images from an image collection that are able to maximize the information perceived by a given user. As main contributions, we first introduce novel metrics that assess the amount of perceived information retained by the user when experiencing a set of images. Given the actual information present in a set of images, which is the volume spanned by the set in the corresponding latent space, we show how to take into account the user’s preferences in such a volume calculation to build a user-centric metric for the perceived information. Finally, we propose a sampling strategy seeking the minimum set of images that maximize the information perceived by a given user. Experiments using the coco dataset show the ability of the proposed approach to accurately integrate user preference while keeping a reasonable diversity in the sampled image set. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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