A Framework for Visual Saliency Detection with Applications to Image Thumbnailing
Abstract
We propose a novel framework for visual saliency detection based on a simple principle: images sharing their global visual appearances are likely to share similar salience. Assuming that an annotated image database is available, we first retrieve the most similar images to the target image; secondly, we build a simple classifier and we use it to generate saliency maps. Finally, we refine the maps and we extract thumbnails. We show that in spite of its simplicity, our framework outperforms state-of-the-art approaches. Another advantage is its ability to deal with visual pop-up and application/task-driven saliency, if appropriately annotated images are available.
Cite
Text
Marchesotti et al. "A Framework for Visual Saliency Detection with Applications to Image Thumbnailing." IEEE/CVF International Conference on Computer Vision, 2009. doi:10.1109/ICCV.2009.5459467Markdown
[Marchesotti et al. "A Framework for Visual Saliency Detection with Applications to Image Thumbnailing." IEEE/CVF International Conference on Computer Vision, 2009.](https://mlanthology.org/iccv/2009/marchesotti2009iccv-framework/) doi:10.1109/ICCV.2009.5459467BibTeX
@inproceedings{marchesotti2009iccv-framework,
title = {{A Framework for Visual Saliency Detection with Applications to Image Thumbnailing}},
author = {Marchesotti, Luca and Cifarelli, Claudio and Csurka, Gabriela},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {2009},
pages = {2232-2239},
doi = {10.1109/ICCV.2009.5459467},
url = {https://mlanthology.org/iccv/2009/marchesotti2009iccv-framework/}
}