Single Image Based Depth Estimation for Maritime Surface Targets

被引：0
作者：
Sun, Jishan [1 ]
Chen, Yaojie [1 ,2 ]
Wang, Wei [1 ]
机构：
[1] Wuhan Univ Sci & Technol, Dept Comp Sci & Technol, Wuhan, Peoples R China
[2] Virtual Simulat Expt Teaching Ctr, Met Ind Proc Natl, Wuhan, Peoples R China
来源：
PROCEEDINGS OF THE 2021 IEEE INTERNATIONAL CONFERENCE ON PROGRESS IN INFORMATICS AND COMPUTING (PIC) | 2021年
关键词：
Single image; Depth estimation; Maritime targets; SC-SfMLearner; Polynomial model;
D O I：
10.1109/PIC53636.2021.9687055
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
When the intelligent water cannon strikes a surface target, it needs to know the distance to the strike target and automatically adjust the strike angle to complete the accurate strike mission. Based on this estimation, the control system of the water cannon would automatically achieve the strike mission. For a universal usage, a monocular image depth estimation method based on SC-SfMLearner is used, which first estimates the depth information of the image from one sample of the real-time video frames and then uses a polynomial fitting model to transfer a depth map into the physical distance in the real world. The experimental results show that the mean square deviation of the predicted distance results in the practical environment for shoreside water targets is between 0.02 and 0.03, and the accuracy rate is above 95 %, which is a good prediction and effectively addresses the accuracy of striking water targets in practical applications.
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收藏
页码：149 / 155
页数：7
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