A prior-based graph for salient object detection

Abstract

Recently, various graph-based methods have be proposed for salient object detection. These algorithms represent image points and their similarity as nodes and edges in a graph. Although the edge structure and weighting are the heart of these methods, the graph construction has not been studied in detail. In this paper, we exploit image priors, including spatial priors, color priors, and a central bias prior, to construct the graph. We connect nodes which are spatially close in the image, nodes which have similar color features, and the boundary nodes along the borders of the image, while weighting edges according to both their color similarity and spatial proximity. Moreover, we propose a ne..