Visual Ego Motion Estimation in Urban Environments based on U-V Disparity

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dc.contributor.author Musleh Lancis, Basam
dc.contributor.author Martín Gómez, David
dc.contributor.author Escalera Hueso, Arturo de la
dc.contributor.author Armingol Moreno, José María
dc.date.accessioned 2016-09-21T10:16:17Z
dc.date.available 2016-09-21T10:16:17Z
dc.date.issued 2012-06-03
dc.identifier.bibliographicCitation Visual Ego Motion Estimation in Urban Environments based on U-V Disparity. Intelligent Vehicles Symposium (IV), 2012 IEEE. : Ieee - The Institute Of Electrical And Electronics Engineers, Inc. Pp. 444-449
dc.identifier.uri http://hdl.handle.net/10016/23607
dc.description.abstract The movement of the vehicle provides useful information for different applications, such as driver assistant systems or autonomous vehicles. This information can be known by means of a GPS, but there are some areas in urban environ ments where the signal is not available, as tunnels or streets with high buildings. A new method for 2D visual ego motion estimation in urban environments is presented in this paper. This method is based on a stereo-vision system where the feature road points are tracked frame to frame in order to estimate the movement of the vehicle, avoiding outliers from dynamic obstacles. The road profile is used to obtain the world coordinates of the feature points as a unique function of its left image coordinates. For these reasons it is only necessary to search feature points in the lower third of the left images. Moreover, the Kalman filter is used as a solution for filtering problem. That is, in some cases, it is necessary to filter raw data due to noise acquisition of time series. The results of the visual ego motion are compared with raw data from a GPS.
dc.description.sponsorship This work was also supported by Spanish Government through the CICYT projects FEDORA (Grant TRA2010-20255-C03-01) and Driver Distraction Detector System (Grant TRA2011-29454-C03-02)
dc.format.extent 7
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher IEEE The Institute Of Electrical And Electronics Engineers, Inc
dc.rights © 2012 IEEE
dc.subject.other Visualization
dc.subject.other Vehicles
dc.subject.other Roads
dc.subject.other Motion estimation
dc.subject.other Global Positioning System
dc.subject.other Trajectory
dc.subject.other Kalman filters
dc.title Visual Ego Motion Estimation in Urban Environments based on U-V Disparity
dc.type conferenceObject
dc.type bookPart
dc.relation.publisherversion http://dx.doi.org/10.1109/IVS.2012.6232183
dc.subject.eciencia Robótica e Informática Industrial
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. TRA2010-20255-C03-01
dc.relation.projectID Gobierno de España. TRA2011-29454-C03-02
dc.type.version acceptedVersion
dc.relation.eventdate 3-7 June 2012
dc.relation.eventplace Alcalá de Henares
dc.relation.eventtitle 2012 IEEE Intelligent Vehicles Symposium
dc.relation.eventtype proceeding
dc.identifier.publicationfirstpage 444
dc.identifier.publicationlastpage 449
dc.identifier.publicationtitle Intelligent Vehicles Symposium (IV), 2012 IEEE
dc.identifier.uxxi CC/0000014611
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