Vehicle Detection from Aerial Imagery - Robotics Institute Carnegie Mellon University

Vehicle Detection from Aerial Imagery

Joshua Gleason, Ara Nefian, Xavier Bouyssounousse, Terrence W. Fong, and George Bebis
Conference Paper, Proceedings of (ICRA) International Conference on Robotics and Automation, pp. 2065 - 2070, May, 2011

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.

BibTeX

@conference{Gleason-2011-7276,
author = {Joshua Gleason and Ara Nefian and Xavier Bouyssounousse and Terrence W. Fong and George Bebis},
title = {Vehicle Detection from Aerial Imagery},
booktitle = {Proceedings of (ICRA) International Conference on Robotics and Automation},
year = {2011},
month = {May},
pages = {2065 - 2070},
publisher = {IEEE},
}