Publication:
Real Time Speed Estimation from Monocular Video

dc.authorscopusid36149699600
dc.authorscopusid15743982700
dc.authorscopusid36117532800
dc.contributor.authorTemiz, M.S.
dc.contributor.authorKülür, S.
dc.contributor.authorDoǧan, S.
dc.date.accessioned2020-06-21T14:29:21Z
dc.date.available2020-06-21T14:29:21Z
dc.date.issued2012
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Temiz] Mahir Serhan, Department of Geomatics Engineering, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Külür] Sitki, Department of Geomatics Engineering, İstanbul Teknik Üniversitesi, Istanbul, Turkey; [Doǧan] Sedat, Department of Geomatics Engineering, Ondokuz Mayis Üniversitesi, Samsun, Turkeyen_US
dc.descriptionESRI; Hexagon; RMIT University, School of Mathematical and Geospatial Sciencesen_US
dc.description.abstractIn this paper, detailed studies have been performed for developing a real time system to be used for surveillance of the traffic flow by using monocular video cameras to find speeds of the vehicles for secure travelling are presented. We assume that the studied road segment is planar and straight, the camera is tilted downward a bridge and the length of one line segment in the image is known. In order to estimate the speed of a moving vehicle from a video camera, rectification of video images is performed to eliminate the perspective effects and then the interest region namely the ROI is determined for tracking the vehicles. Velocity vectors of a sufficient number of reference points are identified on the image of the vehicle from each video frame. For this purpose sufficient number of points from the vehicle is selected, and these points must be accurately tracked on at least two successive video frames. In the second step, by using the displacement vectors of the tracked points and passed time, the velocity vectors of those points are computed. Computed velocity vectors are defined in the video image coordinate system and displacement vectors are measured by the means of pixel units. Then the magnitudes of the computed vectors in the image space are transformed to the object space to find the absolute values of these magnitudes. The accuracy of the estimated speed is approximately ± 1-2 km/h. In order to solve the real time speed estimation problem, the authors have written a software system in C++ programming language. This software system has been used for all of the computations and test applications. © 2012 ISPRS.en_US
dc.identifier.endpage432en_US
dc.identifier.isbn9781629935126
dc.identifier.isbn9781629934297
dc.identifier.isbn9781629935201
dc.identifier.issn1682-1750
dc.identifier.scopus2-s2.0-84924339637
dc.identifier.scopusqualityQ3
dc.identifier.startpage427en_US
dc.identifier.volume39en_US
dc.identifier.wosWOS:000358211200076
dc.language.isoenen_US
dc.publisherInternational Society for Photogrammetry and Remote Sensingen_US
dc.relation.ispartofInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archivesen_US
dc.relation.ispartofseriesInternational Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences
dc.relation.journalXxii Isprs Congress, Technical Commission Iiien_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMonocular Videoen_US
dc.subjectObject Trackingen_US
dc.subjectOptical Flowen_US
dc.subjectSpeed Estimationen_US
dc.subjectTraffic Surveillanceen_US
dc.subjectVideo Imagesen_US
dc.titleReal Time Speed Estimation from Monocular Videoen_US
dc.typeConference Objecten_US
dspace.entity.typePublication

Files