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Fast Multiclass Vehicle Detection on Aerial Images

Liu, Kang and Mattyus, Gellert (2015) Fast Multiclass Vehicle Detection on Aerial Images. IEEE Geoscience and Remote Sensing Letters, 12 (9), pp. 1938-1942. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/LGRS.2015.2439517 ISSN 1545-598X

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Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7122912

Abstract

Detecting vehicles in aerial images provides important information for traffic management and urban planning. Detecting the cars in the images is challenging due to the relatively small size of the target objects and the complex background in man-made areas. It is particularly challenging if the goal is near-real-time detection, i.e., within few seconds, on large images without any additional information, e.g., road database and accurate target size. We present a method that can detect the vehicles on a 21-MPixel original frame image without accurate scale information within seconds on a laptop single threaded. In addition to the bounding box of the vehicles, we extract also orientation and type (car/truck) information. First, we apply a fast binary detector using integral channel features in a soft-cascade structure. In the next step, we apply a multiclass classifier on the output of the binary detector, which gives the orientation and type of the vehicles. We evaluate our method on a challenging data set of original aerial images over Munich and a data set captured from an unmanned aerial vehicle (UAV).

Item URL in elib:https://elib.dlr.de/96765/
Document Type:Article
Title:Fast Multiclass Vehicle Detection on Aerial Images
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Liu, KangUNSPECIFIEDUNSPECIFIED
Mattyus, Gellertgellert.mattyus (at) dlr.deUNSPECIFIED
Date:September 2015
Journal or Publication Title:IEEE Geoscience and Remote Sensing Letters
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:12
DOI :10.1109/LGRS.2015.2439517
Page Range:pp. 1938-1942
Editors:
EditorsEmail
Frery, Alejandro C.acfrery@gmail.com
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1545-598X
Status:Published
Keywords:Detectors;Feature extraction;Histograms;Roads;Training;Vehicle detection;Vehicles;Classification;near real-time;vehicle detection
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - Vabene++ (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Mattyus, Gellert Sandor
Deposited On:24 Jun 2015 09:41
Last Modified:31 Jul 2019 19:53

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