Difference between revisions of "Publications:Evaluation of Fisheye-Camera Based Visual Multi-Session Localization in a Real-World Scenario"
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{{PublicationSetupTemplate|Author=Peter Muehlfellner, Paul Timothy Furgale, Wojciech Derendarz, Roland Philippsen | {{PublicationSetupTemplate|Author=Peter Muehlfellner, Paul Timothy Furgale, Wojciech Derendarz, Roland Philippsen | ||
|PID=642048 | |PID=642048 | ||
| − | |Name= | + | |Name=Mühlfellner, Peter (Volkswagen AG);Furgale, Paul Timothy (ETH Zurich);Derendarz, Wojciech (Volkswagen AG);Philippsen, Roland [rolphi] (Högskolan i Halmstad [2804], Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) [3905], Halmstad Embedded and Intelligent Systems Research (EIS) [3938], Intelligenta system (IS-lab) [3941]) |
|Title=Evaluation of Fisheye-Camera Based Visual Multi-Session Localization in a Real-World Scenario | |Title=Evaluation of Fisheye-Camera Based Visual Multi-Session Localization in a Real-World Scenario | ||
|PublicationType=Conference Paper | |PublicationType=Conference Paper | ||
Revision as of 10:26, 29 April 2014
| Title | Evaluation of Fisheye-Camera Based Visual Multi-Session Localization in a Real-World Scenario |
|---|---|
| Author | Paul Timothy Furgale and Wojciech Derendarz and Roland Philippsen and Peter Mühlfellner |
| Year | 2013 |
| PublicationType | Conference Paper |
| Journal | |
| HostPublication | Intelligent Vehicles Symposium (IV), 2013 IEEE Workshop on Environment Perception and Navigation for Intelligent Vehicles |
| Conference | IEEE Intelligent Vehicles Symposium, June 23-26, 2013, Gold Cost, Australia |
| DOI | http://dx.doi.org/10.1109/IVS.2013.6629447 |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:642048 |
| Abstract | The European V-Charge project seeks to develop fully automated valet parking and charging of electric vehicles using only low-cost sensors. One of the challenges is to implement robust visual localization using only cameras and stock vehicle sensors. We integrated four monocular, wide-angle, fisheye cameras on a consumer car and implemented a mapping and localization pipeline. Visual features and odometry are combined to build and localize against a keyframe-based three dimensional map. We report results for the first stage of the project, based on two months worth of data acquired under varying conditions, with the objective of localizing against a map created offline. © 2013 IEEE. |
