大连海事大学学报 >
2019 , Vol. 45 >Issue 3: 121 - 128
DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2019.03.017
基于机载视觉的内河落水人员发现概率建模
收稿日期: 2019-03-13
修回日期: 2019-04-11
网络出版日期: 2019-04-12
基金资助
国家自然科学基金资助项目(51579204).
Discovery probability modeling of inland waterfall personnel based on airborne vision
Received date: 2019-03-13
Revised date: 2019-04-11
Online published: 2019-04-12
陈雨,肖长诗,周春辉,文元桥,陈芊芊,张义萌 . 基于机载视觉的内河落水人员发现概率建模[J]. 大连海事大学学报, 2019 , 45(3) : 121 -128 . DOI: 10.16411/j.cnki.issn1006-7736.2019.03.017
In order to improve the searching and discovering probability of inland river falling personnel by unmanned aerial vehicle(UAV), a maritime UAV system for inland water searching and rescuing was built. The relationship between UAV flight altitude and camera view field and camera visual imaging was analyzed, and by combining with the theory of visual attention, the regularity of searching people falling into water on the map display screen of ground stations for searchers was studied,and the maximum speed model of UAV and the discovery probability model of dropping personnel were established. The experimental results on the Yangtze River show that the maximum speed model of UAV and the probability model of dropping personnel are reliable for improving the efficiency of inland waterfall personnel.
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