Static and space-time visual saliency detection by self-resemblance.

@article{Seo2009StaticAS,
  title={Static and space-time visual saliency detection by self-resemblance.},
  author={Hae Jong Seo and Peyman Milanfar},
  journal={Journal of vision},
  year={2009},
  volume={9 12},
  pages={15.1-27}
}
We present a novel unified framework for both static and space-time saliency detection. Our method is a bottom-up approach and computes so-called local regression kernels (i.e., local descriptors) from the given image (or a video), which measure the likeness of a pixel (or voxel) to its surroundings. Visual saliency is then computed using the said "self-resemblance" measure. The framework results in a saliency map where each pixel (or voxel) indicates the statistical likelihood of saliency of a… CONTINUE READING
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