Fast road detection and tracking in aerial videos

Zhou,H, Kong,H, Alvarez,J, Creighton,D and Nahavandi,S 2014, Fast road detection and tracking in aerial videos, in Proceedings of 25th Intelligent Vehicles Symposium; IEEE, 2014, IEEE, Piscataway, NJ, pp. 712-718, doi: 10.1109/IVS.2014.6856523.

Attached Files
Name Description MIMEType Size Downloads

Title Fast road detection and tracking in aerial videos
Author(s) Zhou,HORCID iD for Zhou,H
Creighton,DORCID iD for Creighton,D
Nahavandi,SORCID iD for Nahavandi,S
Conference name Intelligent Vehicles. Symposium (25th: 2014: Dearborn, Michigan)
Conference location Dearborn, MI
Conference dates 2014/6/8 - 2014/6/11
Title of proceedings Proceedings of 25th Intelligent Vehicles Symposium; IEEE, 2014
Editor(s) [Unknown]
Publication date 2014
Conference series Intelligent Vehicles Symposium
Start page 712
End page 718
Total pages 6
Publisher IEEE
Place of publication Piscataway, NJ
Summary  We propose a fast approach for detecting and tracking a specific road in aerial videos. It combines adaptive Gaussian Mixture Models (GMMs) to describe road colour distributions, and homography based tracking to track road geometries, where an efficient technique is developed to estimate homography transformations between two frames. Experiments are conducted on videos captured by our unmanned aerial vehicles. All the results demonstrate the effectiveness of our proposed method. We test 1755 frames from 5 videos. Our approach can achieve 0.032 seconds per frame and 2.64% segmentation error for images with 908 × 513 resolutions, on average.
Language eng
DOI 10.1109/IVS.2014.6856523
Field of Research 080103 Computer Graphics
080106 Image Processing
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2014, IEEE
Persistent URL

Connect to link resolver
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 3 times in TR Web of Science
Scopus Citation Count Cited 4 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 654 Abstract Views, 4 File Downloads  -  Detailed Statistics
Created: Fri, 24 Apr 2015, 15:59:01 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact