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Abstract

Vehicle detection from aerial images is becoming an increasingly important research topic in surveillance, traffic monitoring and military applications. The system described in this paper focuses on vehicle detection in rural environments and its applications to oil and gas pipeline threat detection. Automatic vehicle detection by unmanned aerial vehicles (UAV) will replace current pipeline patrol services that rely on pilot visual inspection of the pipeline from low altitude high risk flights that are often restricted by weather conditions. Our research compares a set of feature extraction methods applied for this speciﬁc task and four classification techniques. The best system achieves an average 85% vehicle detection rate and 1800 false alarms per flight hour over a large variety of areas including vegetation, rural roads and buildings, lakes and rivers collected during several day time illuminations and seasonal changes over one year.

Notes

Text Reference

Joshua Gleason, Ara Nefian, Xavier Bouyssounousse, Terrence W. Fong, and George Bebis , "Vehicle Detection from Aerial Imagery," International Conference on Robotics and Automation, May, 2011.

BibTeX Reference

@inproceedings{Fong_2011_6963,
   author = "Joshua Gleason and Ara Nefian and Xavier Bouyssounousse and Terrence W Fong and George Bebis ",
   title = "Vehicle Detection from Aerial Imagery",
   booktitle = "International Conference on Robotics and Automation",
   publisher = "IEEE",
   month = "May",
   year = "2011",
}

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