Car Detection in Aerial Images of Dense Urban Areas

With the ever-increasing demand in the analysis and understanding of aerial images in order to remotely recognize targets, this paper introduces a robust system for the detection and localization of cars in images captured by air vehicles and satellites. The system adopts a sliding-window approach....

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2018-02, Vol.54 (1), p.51-63
Main Authors: ElMikaty, Mohamed, Stathaki, Tania
Format: Article
Language:English
Subjects:
Airborne Imagery
Automatic Target Recognition
Automobiles
Car Detection
Computational modeling
Demand analysis
Feature extraction
Image color analysis
Image detection
Image edge detection
Roads
Satellite imagery
Target recognition
Urban areas
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Summary:With the ever-increasing demand in the analysis and understanding of aerial images in order to remotely recognize targets, this paper introduces a robust system for the detection and localization of cars in images captured by air vehicles and satellites. The system adopts a sliding-window approach. It compromises a window-evaluation and a window-classification subsystems. The performance of the proposed framework was evaluated on the Vaihingen dataset. Results demonstrate its superiority to the state of the art.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2017.2732832