标题：
Saliency Detection Method Using Adaptive Background Template and Spatial Prior
点击次数：
所属单位：
计算机科学与技术学院/人工智能学院/软件学院
发表刊物：
Zidonghua Xuebao Acta Auto. Sin.
摘要：
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. Copyright © 2017 Acta Automatica Sinica. All rights reserved.
ISSN号：
0254-4156
是否译文：
否
发表时间：
2017-10-01
合写作者：
Lin, Hua-Feng,Liu, Guo-Dong,Liang, Da-Chuan,Li, Dong-Min
通讯作者：
李静
发表时间：
2017-10-01
学位：工学博士学位
职称：副教授
所在单位：计算机科学与技术学院/人工智能学院/软件学院