Salient object detection using scene layout estimation

In this paper we present a method of visual salient region detection based on depth maps estimated from 2D images. Depth estimation aims at better understanding spatial scene layout and relationship between objects. From depth maps we extract geometry related features that are further fused with color contrast. We solve saliency detection problem in segment-wise domain that allows prediction of objects rather than separate pixels. Modelling of saliency is done using conditional random field that allows for pairwise dependencies of segments. Parameters tuning is done by learning from ground-truth data. The evaluation has shown feasibility and good performance of the proposed method.