Visual attention based model for target detection in large-field images

作     者：Lining Gao Fukun Bi Jian Yang 

作者机构：Department of Electronic Engineering Tsinghua University Beijing 100084 P. R. China School of Information and Electronics Beijing Institute of Technology Beijing 100081 E R. China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2011年第22卷第1期

页      面：150-156页

核心收录：

学科分类：0402[教育学-心理学(可授教育学、理学学位）] 04[教育学] 0839[工学-网络空间安全] 08[工学] 040201[教育学-基础心理学] 

基　　金：supported by the National Natural Science Foundation of China (40871157) 

主　　题：target detection visual attention salient region classifier fusion. 

摘      要：It is of great significance to rapidly detect targets in large-field remote sensing images,with limited computation *** relative achievements of visual attention in perception psychology,this paper proposes a hierarchical attention based model for target ***,at the preattention stage,before getting salient regions,a fast computational approach is applied to build a saliency *** that,the focus of attention（FOA） can be quickly obtained to indicate the salient ***,at the attention stage,under the FOA guidance,the high-level visual features of the region of interest are extracted in ***,at the post-attention stage,by integrating these parallel and independent visual attributes,a decision-template based classifier fusion strategy is proposed to discriminate the task-related targets from the other extracted salient *** comparison,experiments on ship detection are done for validating the effectiveness and feasibility of the proposed model.