What is «saliency» in computer vision?

Visual Saliency is the capability of vision system to select distinctive parts of scene and reduce the amount of visual data that need to be processed.

Visual salience (or visual saliency) is the distinct subjective perceptual quality which makes some items in the world stand out from their neighbors and immediately grab our attention.

Saliency is a kind of image segmentation.

The term saliency has been used in different contexts, but tends to mean «interestingness».
For example, green squares on a black background have a high saliency, but the one red square among them has an even higher saliency.
In addition, a square moving through an otherwise still scene is very salient.

Until recently, most computer vision algorithms have relied on brute-force, systematic scanning of images from left-to-right and top-to bottom when attempting to locate objects of interest.
Visual salience provides a relatively inexpensive and rapid mechanism to select a few likely candidates and eliminate obvious clutter (Itti & Koch, 2000; Navalpakkam & Itti, 2005).

Applications of computational models of visual salience include, among many others:

  • Automatic target detection (e.g., finding traffic signs along the road or military vehicles in a savanna; Itti & Koch, 2000);
  • Robotics (using salient objects in the environment as navigation landmarks; Frintrop et al., 2006; Siagian & Itti, 2007);
  • Image and video compression (e.g., giving higher quality to salient objects at the expense of degrading background clutter; Maeder et al., 1996; Itti, 2004);
  • Automatic cropping/centering of images for display on small portable screens (Le Meur et al., 2006);
  • Finding tumors in mammograms (Hong & Brady, 2003);