Title
Vision based long range object detection and tracking for unmanned surface vehicle
Abstract
A real time vision based long range object detection and tracking algorithm for unmanned surface vehicles (USV) is proposed in this paper. HD image (2736 × 2192) is utilised in this work to obtain high accuracy for the object distance estimation. With handling such high resolution images for real time performance, we propose a coarse to fine approach, which firstly estimates the sea surface plane and locations of objects coarsely on lower resolution images corresponding to the HD images, then the detected coarse locations or regions of interest (ROI) are projected to the original HD image, finally stereo matching is preformed in the original image only on these extracted ROI, which renders more accurate 3D information for localizing the objects on the open sea. In the tracking, we propose to combine the target tracking based on 2D image with the constrained template matching to compute the depth, which demonstrates a more robust and accurate performance. Experimental results with our own dataset verify the high efficiency of our proposed method.
Year
DOI
Venue
2015
10.1109/ICCIS.2015.7274604
2015 IEEE 7th International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM)
Keywords
Field
DocType
object tracking,unmanned surface vehicle,real time vision based long range object detection,USV,HD image,object distance estimation,high resolution images,regions of interest,ROI,stereo matching
Template matching,Stereo matching,Object detection,Computer vision,Viola–Jones object detection framework,Unmanned surface vehicle,Object-class detection,Real time vision,Vision based,Artificial intelligence,Engineering
Conference
ISSN
ISBN
Citations 
2326-8123
978-1-4673-7337-1
0
PageRank 
References 
Authors
0.34
7
7
Name
Order
Citations
PageRank
Han Wang114822.31
Xiaozheng Mou222.11
Wei Mou3133.79
Shenghai Yuan4104.82
Soner Ulun510.71
Shuai Yang6188.46
Bok-Suk Shin7689.27