Detection of cars in high-resolution aerial images of complex urban environments
File(s)
Accepted version
Author(s)
ElMikaty, M
Stathaki, P
Type
Journal Article
Abstract
Detection of small targets, more specifically cars, in aerial images of urban scenes, has various applications in several domains, such as surveillance, military, remote sensing, and others. This is a tremendously challenging problem, mainly because of the significant interclass similarity among objects in urban environments, e.g., cars and certain types of nontarget objects, such as buildings' roofs and windows. These nontarget objects often possess very similar visual appearance to that of cars making it hard to separate the car and the noncar classes. Accordingly, most past works experienced low precision rates at high recall rates. In this paper, a novel framework is introduced that achieves a higher precision rate at a given recall than the state of the art. The proposed framework adopts a sliding-window approach and it consists of four stages, namely, window evaluation, extraction and encoding of features, classification, and postprocessing. This paper introduces a new way to derive descriptors that encode the local distributions of gradients, colors, and texture. Image descriptors characterize the aforementioned cues using adaptive cell distributions, wherein the distribution of cells within a detection window is a function of its dominant orientation, and hence, neither the rotation of the patch under examination nor the computation of descriptors at different orientations is required. The performance of the proposed framework has been evaluated on the challenging Vaihingen and Overhead Imagery Research data sets. Results demonstrate the superiority of the proposed framework to the state of the art.
Date Issued
2017-10-01
Date Acceptance
2017-06-03
Citation
IEEE Transactions on Geoscience and Remote Sensing, 2017, 55 (10), pp.5913-5924
ISSN
0196-2892
Publisher
Institute of Electrical and Electronics Engineers
Start Page
5913
End Page
5924
Journal / Book Title
IEEE Transactions on Geoscience and Remote Sensing
Volume
55
Issue
10
Copyright Statement
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Identifier
https://ieeexplore.ieee.org/document/7982952
Subjects
Science & Technology
Physical Sciences
Technology
Geochemistry & Geophysics
Engineering, Electrical & Electronic
Remote Sensing
Imaging Science & Photographic Technology
Engineering
Airborne imagery
automatic target recognition
car detection
VEHICLE DETECTION
CLASSIFICATION
RECOGNITION
HOG
0404 Geophysics
0906 Electrical and Electronic Engineering
0909 Geomatic Engineering
Geological & Geomatics Engineering
Publication Status
Published
Date Publish Online
2017-07-17