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Proceedings Paper

Robust obstacle detection for unmanned surface vehicles
Author(s): Yueming Qin; Xiuzhi Zhang
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Paper Abstract

Obstacle detection is of essential importance for Unmanned Surface Vehicles (USV). Although some obstacles (e.g., ships, islands) can be detected by Radar, there are many other obstacles (e.g., floating pieces of woods, swimmers) which are difficult to be detected via Radar because these obstacles have low radar cross section. Therefore, detecting obstacle from images taken onboard is an effective supplement. In this paper, a robust vision-based obstacle detection method for USVs is developed. The proposed method employs the monocular image sequence captured by the camera on the USVs and detects obstacles on the sea surface from the image sequence. The experiment results show that the proposed scheme is efficient to fulfill the obstacle detection task.

Paper Details

Date Published: 8 March 2018
PDF: 6 pages
Proc. SPIE 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 106111E (8 March 2018); doi: 10.1117/12.2285607
Show Author Affiliations
Yueming Qin, Yichang Testing Technique Research Institute (China)
Xiuzhi Zhang, Yichang Testing Technique Research Institute (China)


Published in SPIE Proceedings Vol. 10611:
MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Nong Sang; Jie Ma; Zhong Chen, Editor(s)

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