Leveraging Spatial Context Disparity for Power Line Detection
Pan, Chaofeng1,4; Shan, Haotian1,4; Cao, Xianbin1; Li, Xuelong2,3; Wu, Dapeng1,5
刊名cognitive computation
2017-08-02
页码1-14
ISSN号18669956
通讯作者cao, xianbin (xbcao@buaa.edu.cn)
产权排序2
英文摘要

for the safety of low flying aircraft, it will become increasingly important that an aircraft should have the ability to detect and avoid small obstacles in the low flying environment. in recent years, using context information to assist in detecting power lines has shown great potential to better detect power lines at a remote distance. therefore, how to adequately use the context information for a better detection is a hot issue of concern. this paper proposes a novel auxiliary assisted power line detection method, in which the spatial context disparity of auxiliaries is quantitatively and uniformly evaluated for the first time. as a cognitive strategy, the spatial context disparity depends on two factors, the spatial context peakedness and the spatial context difference. with this cognitive method, objects that achieve high spatial context disparity scores are more suitable for being the auxiliaries of the power lines. experimental results show that, owing to the spatial context disparity, the proposed method can acquire proper auxiliaries with abundant context information to support the detection, so that better power line detections are achieved comparing to traditional power line detection methods. the proposed power line detection method, which can automatically choose the optimal auxiliaries, is effective and has the potential for practical use in ensuring the flight safety of unmanned air vehicles (uavs) in the low flying environment. © 2017 springer science+business media, llc

收录类别EI
语种英语
内容类型期刊论文
源URL[http://ir.opt.ac.cn/handle/181661/29204]  
专题西安光学精密机械研究所_光学影像学习与分析中心
作者单位1.School of Electronics and Information Engineering, Beihang University, and National Key Laboratory of CNS/ATM, Beijing; 100191, China
2.The Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an; Shaanxi; 710119, China
3.The University of Chinese Academy of Sciences, Beijing; 100049, China
4.School of Electronics and Information Engineering, Beihang University, Beijing Laboratory for General Aviation Technology, Beijing; 100191, China
5.University of Florida, Gainesville; FL, United States
推荐引用方式
GB/T 7714
Pan, Chaofeng,Shan, Haotian,Cao, Xianbin,et al. Leveraging Spatial Context Disparity for Power Line Detection[J]. cognitive computation,2017:1-14.
APA Pan, Chaofeng,Shan, Haotian,Cao, Xianbin,Li, Xuelong,&Wu, Dapeng.(2017).Leveraging Spatial Context Disparity for Power Line Detection.cognitive computation,1-14.
MLA Pan, Chaofeng,et al."Leveraging Spatial Context Disparity for Power Line Detection".cognitive computation (2017):1-14.
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