De-emphasis of distracting image regions using texture power maps

We present a post-processing technique that selectively reduces the salience of distracting regions in an image. Computational models of attention predict that texture variation influences bottom-up attention mechanisms. Our method reduces the spatial variation of texture using power maps, high-order features describing local frequency content in an image. Modification of power maps results in effective regional de-emphasis. We validate our results quantitatively via a human subject search experiment and qualitatively with eye tracking data.

• Type: Conference
• Year: 2005
• Where: APGV
• Authors: Sara L. Su, Frédo Durand, Maneesh Agrawala
• Keywords: APGV 2005, Bottom-up Attention Mechanisms, Power Maps, Texture Variation