Salient Object Detection Via Deformed Smoothness Constraint
Xiyin Wu, Xiaodi Ma, Jinxia Zhang, Andong Wang, Zhong Jin · 2018
In recent years, various graph-based salient object detection methods have been successfully proposed. Since existing methods may miss some object regions with low contrast to background, a novel propagation model via deformed smoothness constraint is proposed to address this problem. By regularizing nodes and their neighbors locally, the deformed smoothness constraint is able to prevent erroneous label propagation. Thus, the object regions with low contrast to background can be emerged. Besides, the deformed smoothness constraint is further utilized in a map refinement model, which can suppress the background noises in label propagation result. Experiments on three public datasets show that the proposed method outperforms eleven state-of-the-art salient object detection methods.