Contrast based Saliency Detection via Manifold Ranking

摘要

Saliency detection has been widely studied in computer vision. In this paper we propose a two-steps method combining contrast assumption and ranking technology to detect saliency region. Firstly, We use the traditional contrast assumption to find foregroundcues. Then we rank the nodes with labeled contrast cues by graph-based manifold ranking. We experiment with our method on a large public data set. Our results show the effectiveness of our method, and perform better compared to recent state-of-the-art methods.