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Distance Measurement of Underwater Target Based on Stereo Vision
Lin S(林森); Li WT(李文涛); Cong Y(丛杨); Tang YD(唐延东)
作者部门机器人学研究室
会议名称7th IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017
会议日期July 31 - August 4, 2017
会议地点Hawaii, USA
会议主办者IEEE Robotics and Automation Society
会议录名称2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017
出版者IEEE
出版地New York
2017
页码97-102
收录类别EI ; CPCI(ISTP)
EI收录号20183905873465
WOS记录号WOS:000447628700019
产权排序1
ISBN号978-1-5386-0489-2
关键词Stereo Vision Remote Operated Vehicle Distance Measurement Underwater Interaction
摘要

An underwater object location method based on binocular stereo vision and artificial auxiliary interaction is proposed. Firstly, the calibration principle and basic model of binocular stereo vision are given, and the relationship between binocular disparity and depth is deduced in detail. Then, a special underwater camera (Nano SeaCam) is used, and we can calibrate the camera directly underwater. After that, the parameters of the camera are obtained to rectify the underwater images. Further, according to the characteristics of underwater ROV (Remote Operated Vehicle), we use the method of artificial interaction to select the corresponding pixels of left and right view images, and then use the distance measurement algorithm to calculate the target distance. The experimental results show that this method can achieve the proper effect of measuring distance underwater, and the accuracy can meet the practical requirements, which is feasible and efficient.

语种英语
引用统计
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/21347
专题机器人学研究室
通讯作者Lin S(林森)
作者单位1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.School of Electronic and Information Engineering, Liaoning Technical University, Huludao, China
推荐引用方式
GB/T 7714
Lin S,Li WT,Cong Y,et al. Distance Measurement of Underwater Target Based on Stereo Vision[C]//IEEE Robotics and Automation Society. New York:IEEE,2017:97-102.
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