Ranking regions of visual saliency in RGB-D content

Abstract

Effective immersion takes place when the user can relate to the 3D environment presented and interact with key objects. Efficiently predicting which objects in a scene are in the user's attention, without using additional hardware, such as eye tracking solutions, provides an opportunity for creating more immersive scenes in real time and at lower costs. This is nonetheless algorithmically challenging. In this paper, we are proposing a technique that efficiently and effectively identifies the most salient objects in a scene. We show how it accurately matches user selection within 0.04s and is over 95% faster than other saliency algorithms while also providing a ranking of the most salient segments in a scene.