自动化学报2017，Vol.43Issue(10)：1736-1748,13.DOI:10.16383/j.aas.2017.c160431
基于自适应背景模板与空间先验的显著性物体检测方法
Saliency Detection Method Using Adaptive Background Template and Spatial Prior
摘要
Abstract
Due to its effectiveness of identifying salient object while suppressing the background,boundary prior has been widely used in saliency detection recently.However,if the locations of salient regions are near the image border,the existing methods would not be suitable.In order to improve the robustness of saliency detection,we propose an improved saliency detection method using adaptive background template and spatial prior.Firstly,according to the rarity of salient object in the color space,a selection strategy is presented to establish the adaptive background template by removing the potential saliency superpixels from the image border regions,and a saliency map is obtained.A propagation mechanism based on K-means algorithm is designed for maintaining the neighborhood coherence of the above saliency map.Secondly,according to the aggregation of salient object,a new spatial prior is presented to integrate the saliency detection results by aggregating two complementary measures such as image center preference and the background template exclusion.Finally,the final salient map is obtained by fusing the above two salient maps.Quantitative experiments on four available datasets MSRA-1000,SOD,ECSSD and new constructed CBD demonstrate that our method outperforms other state-of-the-art saliency detection approaches.关键词
显著性检测/背景模板/传播机制/空间先验Key words
Saliency detection/background template/propagation mechanism/spatial prior引用本文复制引用
林华锋,李静,刘国栋,梁大川,李东民..基于自适应背景模板与空间先验的显著性物体检测方法[J].自动化学报,2017,43(10):1736-1748,13.基金项目
中央高校基本科研业务费专项资金(NS2015092)资助 （NS2015092）
Supported by Fundamental Research Funds for the Central Universities (NS2015092) （NS2015092）
