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Automatic Car Counting Method for Unmanned Aerial Vehicle Images.
- Source :
-
IEEE Transactions on Geoscience & Remote Sensing . Mar2014, Vol. 52 Issue 3, p1635-1647. 13p. - Publication Year :
- 2014
-
Abstract
- This paper presents a solution to solve the car detection and counting problem in images acquired by means of unmanned aerial vehicles (UAVs). UAV images are characterized by a very high spatial resolution (order of few centimeters), and consequently by an extremely high level of details which calls for appropriate automatic analysis methods. The proposed method starts with a screening step of asphalted zones in order to restrict the areas where to detect cars and thus to reduce false alarms. Then, it performs a feature extraction process based on scalar invariant feature transform thanks to which a set of keypoints is identified in the considered image and opportunely described. Successively, it discriminates between keypoints assigned to cars and all the others, by means of a support vector machine classifier. The last step of our method is focused on the grouping of the keypoints belonging to the same car in order to get a “one keypoint-one car” relationship. Finally, the number of cars present in the scene is given by the number of final keypoints identified. The experimental results obtained on a real UAV scene characterized by a spatial resolution of 2 cm show that the proposed method exhibits a promising car counting accuracy. [ABSTRACT FROM PUBLISHER]
- Subjects :
- *DRONE aircraft
*MILITARY airplanes
*REMOTE sensing
*ALGORITHMS
*PIXELS
*ASPHALT
Subjects
Details
- Language :
- English
- ISSN :
- 01962892
- Volume :
- 52
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Geoscience & Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 101186563
- Full Text :
- https://doi.org/10.1109/TGRS.2013.2253108