Saliency region and density maximization for salient object detection

Abstract

In this paper, we propose an alternative salient object detection method based on maximum saliency region and density. The proposed approach can automatically detect the salient object with a well-defined boundary. Saliency region and density maximization is used as the quality function to find the optimal window containing a salient object. And for efficiently executing window search, a branch-and-bound search algorithm based on saliency region and density is proposed. Then the located window is used to initialize the GrabCut method, and the salient object with a well- defined boundary is extracted through applying GrabCut. Experimental results show that the proposed salient object detection approach outperforms the state-of-the-art methods.