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Proceedings Paper

Vehicle detection and orientation estimation using the radon transform
Author(s): Rengarajan Pelapur; Filiz Bunyak; Kannappan Palaniappan; Gunasekaran Seetharaman
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Paper Abstract

Determining the location and orientation of vehicles in satellite and airborne imagery is a challenging task given the density of cars and other vehicles and complexity of the environment in urban scenes almost anywhere in the world. We have developed a robust and accurate method for detecting vehicles using a template-based directional chamfer matching, combined with vehicle orientation estimation based on a refined segmentation, followed by a Radon transform based profile variance peak analysis approach. The same algorithm was applied to both high resolution satellite imagery and wide area aerial imagery and initial results show robustness to illumination changes and geometric appearance distortions. Nearly 80% of the orientation angle estimates for 1585 vehicles across both satellite and aerial imagery were accurate to within 15◦ of the ground truth. In the case of satellite imagery alone, nearly 90% of the objects have an estimated error within ±1.0° of the ground truth.

Paper Details

Date Published: 14 June 2013
PDF: 13 pages
Proc. SPIE 8747, Geospatial InfoFusion III, 87470I (14 June 2013); doi: 10.1117/12.2016407
Show Author Affiliations
Rengarajan Pelapur, Univ. of Missouri-Columbia (United States)
Filiz Bunyak, Univ. of Missouri-Columbia (United States)
Kannappan Palaniappan, Univ. of Missouri-Columbia (United States)
Gunasekaran Seetharaman, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 8747:
Geospatial InfoFusion III
Matthew F. Pellechia; Richard J. Sorensen; Kannappan Palaniappan, Editor(s)

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