液晶与显示2016，Vol.31Issue(7)：726-732,7.DOI:10.3788/YJYXS20163107.0726
基于结构标签学习的显著性目标检测
Salient object detection based on structured labels learning
摘要
Abstract
This paper proposes a salient object detection method based on structured labels learning, applying a structured learning method to salient object detection.Firstly,we get a fixed rectangular region randomly from the local image which includes the labeling,and record the corresponding struc-tured labels.Then,a collection of decision trees is built by using the regional features which includes the structured labels.Finally,the final saliency map is captured by using the supervised learning ap-proach.Experiments show that our method can detect the salient objects accurately,and the AUC scores are 0.891 8 and 0.705 2 on the MSRA5000 and BSD300 datasets,the result shows that our method can achieve good effect in salient object detection.关键词
显著目标检测/结构标签/决策树/监督学习Key words
salient object detection/structured labels/decision trees/supervised learning分类
信息技术与安全科学引用本文复制引用
程藜,吴谨,朱磊..基于结构标签学习的显著性目标检测[J].液晶与显示,2016,31(7):726-732,7.基金项目
国家自然科学基金青年项目(No．61502358) Supported by National Natural Science Foundation of China(No．61502358) （No．61502358）
