Color boosted visual saliency detection and its application to image classification

摘要

For many applications in graphics, design and human computer interaction, it is essential to reliably estimate the visual saliency of images. In this paper, we propose a visual saliency detection method that combines the respective merits of color saliency boosting and global region based contrast schemes to achieve more accurate saliency maps. Our method is compared with existing saliency detection methods when evaluated using four public available datasets. Experimental results show that our method consistently outperformed current state-of-the-art methods on predicting human fixations. We also demonstrate how the extracted saliency map can be used for image classification.