<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>2439</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>95</pageFirst>
    <pageLast>101</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>IV-2/W7</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2019-09-16</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Rule-Based Mapping of Parked Vehicles using Aerial Image Sequences</title>
    <abstract language="eng">Mapping of parking spaces in cities is a prerequisite for future applications in parking space management like community-based parking. Although terrestrial or vehicle based sensors will be the favorite data source for parking space mapping, airborne monitoring can play a role in building up city wide basis maps which include also parking spaces on ancillary and suburban roads. We present a novel framework for automatic city wide classification of vehicles in moving, stopped and parked using aerial image sequences and information from a road database. The time span of observation of a specific vehicle during an image sequence is usually not long enough to decide unambiguously, whether a vehicle stopped e.g. before a traffic light or is parking along the road. Thus, the workflow includes a vehicle detection and tracking method as well as a rule-based fuzzy-logic workflow for the classification of vehicles. The workflow classifies stopped and parked vehicles by including the neighbourhood of each vehicle via a Delaunay-Graph. The presented method reaches correctness values of around 86.3%, which is demonstrated using three different aerial image sequences. The results depend on several factors like detection quality and road database accuracy.</abstract>
    <parentTitle language="eng">ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences</parentTitle>
    <identifier type="doi">doi.org/10.5194/isprs-annals-IV-2-W7-95-2019</identifier>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Julia Knöttner</author>
    <author>Dominik Rosenbaum</author>
    <author>Franz Kurz</author>
    <author>Ansgar Brunn</author>
    <author>Peter Reinartz</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Aerial Image Sequences</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Vehicle Detection</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Vehicle Tracking</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Parking Space Mapping</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fuzzy Logic</value>
    </subject>
    <collection role="institutes" number="fkv">Fakultät Kunststofftechnik und Vermessung</collection>
    <collection role="Autoren" number="brunn">Ansgar Brunn</collection>
  </doc>
</export-example>
