Exploiting local and global patch rarities for saliency detection

9 years 2 months ago
Exploiting local and global patch rarities for saliency detection
We introduce a saliency model based on two key ideas. The first one is considering local and global image patch rarities as two complementary processes. The second one is based on our observation that for different images, one of the RGB and Lab color spaces outperforms the other in saliency detection. We propose a framework that measures patch rarities in each color space and combines them in a final map. For each color channel, first, the input image is partitioned into non-overlapping patches and then each patch is represented by a vector of coefficients that linearly reconstruct it from a learned dictionary of patches from natural scenes. Next, two measures of saliency (Local and Global) are calculated and fused to indicate saliency of each patch. Local saliency is distinctiveness of a patch from its surrounding patches. Global saliency is the inverse of a patch’s probability of happening over the entire image. The final saliency map is built by normalizing and fusing local...
Ali Borji, Laurent Itti
Added 28 Sep 2012
Updated 28 Sep 2012
Type Journal
Year 2012
Where CVPR
Authors Ali Borji, Laurent Itti
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