Research Article
Real-Time Obstacle Detection Based on Monocular Vision for Unmanned Surface Vehicles
@INPROCEEDINGS{10.1007/978-3-030-57115-3_14, author={Zhang Rui and Liu Jingyi and Li Hengyu and Cheng Qixing}, title={Real-Time Obstacle Detection Based on Monocular Vision for Unmanned Surface Vehicles}, proceedings={Bio-inspired Information and Communication Technologies. 12th EAI International Conference, BICT 2020, Shanghai, China, July 7-8, 2020, Proceedings}, proceedings_a={BICT}, year={2020}, month={8}, keywords={Obstacle detection Unmanned surface vehicle Computer vision}, doi={10.1007/978-3-030-57115-3_14} }- Zhang Rui
Liu Jingyi
Li Hengyu
Cheng Qixing
Year: 2020
Real-Time Obstacle Detection Based on Monocular Vision for Unmanned Surface Vehicles
BICT
Springer
DOI: 10.1007/978-3-030-57115-3_14
Abstract
The reliable obstacle detection is a challenging task in autonomous navigation of unmanned surface vehicles. In this paper, we present a novel real-time obstacles detection based on monocular vision which can effectively tell apart obstacles on the sea surface from complex background. The main innovation of this paper is to propose a water-boundary-line algorithm based on semantic segmentation and random sample consistency line fitting. And use a simple and effective saliency detection method based on background prior and foreground prior to detect obstacles under the water-boundary-line. Our method can efficiently and quickly obtain obstacle information from images captured by shipborne cameras, and it has the ability to process more than 33 frames/s.
