elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Vehicle Detection in Very High Resolution Satellite Images of City Areas

Leitloff, Jens and Hinz, Stefan and Stilla, Uwe (2010) Vehicle Detection in Very High Resolution Satellite Images of City Areas. IEEE Transactions on Geoscience and Remote Sensing, 48 (7), pp. 2795-2806. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/TGRS.2010.2043109 ISSN 0196-2892

[img] PDF - Registered users only
1MB

Official URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5440956

Abstract

Current traffic research is mostly based on data from fixed-installed sensors like induction loops, bridge sensors, and cameras. Thereby, the traffic flow on main roads can partially be acquired, while data from the major part of the entire road network are not available. Today's optical sensor systems on satellites provide large-area images with 1-m resolution and better, which can deliver complement information to traditional acquired data. In this paper, we present an approach for automatic vehicle detection from optical satellite images. Therefore, hypotheses for single vehicles are generated using adaptive boosting in combination with Haar-like features. Additionally, vehicle queues are detected using a line extraction technique since grouped vehicles are merged to either dark or bright ribbons. Utilizing robust parameter estimation, single vehicles are determined within those vehicle queues. The combination of implicit modeling and the use of a priori knowledge of typical vehicle constellation leads to an enhanced overall completeness compared to approaches which are only based on statistical classification techniques. Thus, a detection rate of over 80% is possible with very high reliability. Furthermore, an approach for movement estimation of the detected vehicle is described, which allows the distinction of moving and stationary traffic. Thus, even an estimate for vehicles' speed is possible, which gives additional information about the traffic condition at image acquisition time.

Item URL in elib:https://elib.dlr.de/64468/
Document Type:Article
Title:Vehicle Detection in Very High Resolution Satellite Images of City Areas
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Leitloff, Jensjens.leitloff (at) dlr.deUNSPECIFIED
Hinz, Stefanstefan.hinz (at) kit.eduUNSPECIFIED
Stilla, Uwestilla (at) tum.deUNSPECIFIED
Date:July 2010
Journal or Publication Title:IEEE Transactions on Geoscience and Remote Sensing
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:48
DOI :10.1109/TGRS.2010.2043109
Page Range:pp. 2795-2806
Editors:
EditorsEmail
Ruf, Christophertgrs-editor@ieee.org
Publisher:IEEE - Institute of Electrical and Electronics Engineers
Series Name:IEEE Transactions on Geoscience and Remote Sensing
ISSN:0196-2892
Status:Published
Keywords:Adaptive boosting (AdaBoost) parameter estimation satellite imagery 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), V - ARGOS (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Leitloff, Jens
Deposited On:28 Jun 2010 11:30
Last Modified:08 Mar 2018 18:34

Repository Staff Only: item control page

Browse
Search
Help & Contact
Information
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.