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A framework for visual saliency detection with applications to image thumbnailing

Luca Marchesotti, Claudio Cifarelli, Gabriela Csurka
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.
ICCV 2009 (12th IEEE International Conference on Computer Vision), Kyoto, Japan, Sept 29th - Oct 2nd, 2009


2009-020Final.pdf (631.12 kB)