Saliency Detection Based on Depth Selective Difference and Background Prior

Depth information plays an important role in the human visual system. Based on color and depth features, a saliency detection model was proposed in this paper based on depth selective difference and prior background prior. First, the proportion of color and depth features was adjusted according to the quality of depth map. Second, the saliency map based on depth selectivity difference was calculated according to the intrinsic characteristics of depth map.Then, based on the acquired boundary background set and depth prior background set, a saliency detection method was presented based on prior background prior. Finally, the two saliency maps obtained in the previous period were fused and adjusted, and the saliency maps were optimized to obtain the final saliency detection result. Experiments on two publicly available datasets show that the proposed method performs better than that of other state-of-the-art approaches.