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

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dc.affiliation.dptoUC3M. Departamento de Ingeniería de Sistemas y Automáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Laboratorio de Sistemas Inteligenteses
dc.contributor.authorMusleh Lancis, Basam
dc.contributor.authorMartín Gómez, David
dc.contributor.authorEscalera Hueso, Arturo de la
dc.contributor.authorArmingol Moreno, José María
dc.date.accessioned2016-09-21T10:16:17Z
dc.date.available2016-09-21T10:16:17Z
dc.date.issued2012-06-03
dc.description.abstractThe 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.en
dc.description.sponsorshipThis 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)en
dc.format.extent7
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationVisual 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. 444-449en
dc.identifier.publicationfirstpage444
dc.identifier.publicationlastpage449
dc.identifier.publicationtitleIntelligent Vehicles Symposium (IV), 2012 IEEE
dc.identifier.urihttps://hdl.handle.net/10016/23607
dc.identifier.uxxiCC/0000014611
dc.language.isoeng
dc.publisherIEEE The Institute Of Electrical And Electronics Engineers, Inc
dc.relation.eventdate3-7 June 2012
dc.relation.eventplaceAlcalá de Henareses
dc.relation.eventtitle2012 IEEE Intelligent Vehicles Symposiumen
dc.relation.projectIDGobierno de España. TRA2010-20255-C03-01es
dc.relation.projectIDGobierno de España. TRA2011-29454-C03-02es
dc.relation.publisherversionhttp://dx.doi.org/10.1109/IVS.2012.6232183es
dc.rights© 2012 IEEE
dc.rights.accessRightsopen access
dc.subject.ecienciaRobótica e Informática Industriales
dc.subject.otherVisualizationen
dc.subject.otherVehiclesen
dc.subject.otherRoadsen
dc.subject.otherMotion estimationen
dc.subject.otherGlobal Positioning Systemen
dc.subject.otherTrajectoryen
dc.subject.otherKalman filtersen
dc.titleVisual Ego Motion Estimation in Urban Environments based on U-V Disparityen
dc.typeconference paper*
dc.type.hasVersionAM*
dspace.entity.typePublication
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