Automatic estimation of vehicle speed from uncalibrated video sequences

dc.contributor.author	Γραμματικόπουλος, Λάζαρος	el
dc.contributor.author	Καρράς, Γιώργος	el
dc.contributor.author	Πέτσα, Έλλη	el
dc.date.accessioned	2015-01-29T09:14:14Z
dc.date.available	2015-01-29T09:14:14Z
dc.date.issued	2015-01-29
dc.identifier.uri	http://hdl.handle.net/11400/5016
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.subject	Video sequences
dc.subject	Road surface
dc.subject	Vehicle
dc.subject	Ακολουθίες βίντεο
dc.subject	Οδόστρωμα
dc.subject	Όχημα
dc.title	Automatic estimation of vehicle speed from uncalibrated video sequences	en
heal.type	conferenceItem
heal.classification	Technology
heal.classification	Photogrammetry
heal.classification	Τεχνολογία
heal.classification	Φωτογραμμετρία
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85133147
heal.classificationURI	http://skos.um.es/unescothes/C02980
heal.classificationURI	N/A-Τεχνολογία
heal.classificationURI	N/A-Φωτογραμμετρία
heal.language	en
heal.access	free
heal.recordProvider	Τ.Ε.Ι. Αθήνας, Σχολή Τεχνολογικών Εφαρμογών, Τμήμα Μηχανικών Πληροφορικής και Μηχανικών Τοπογραφίας & Γεωπληροφορικής	el
heal.publicationDate	2005-11-03
heal.bibliographicCitation	Grammatikopoulos, L., Karras, G. and Petsa, E. (2005). Automatic estimation of vehicle speed from uncalibrated video sequences. Proceedings of the FIG-ISPRS-ICA International Symposium on Modern Technologies, Education & Professional Practice in Geodesy & Related Fields, Sofia, 03-04/11/2005, pp. 332-338. Available from: http://portal.survey.ntua.gr/main/labs/photo/staff/gkarras/Karras_Sofia_2005.pdf.	en
heal.abstract	Video sequences of road and traffic scenes are currently used for various purposes, such as studies of the traffic character of freeways. The task here is to automatically estimate vehicle speed from video sequences, acquired with a downward tilted camera from a bridge. Assuming that the studied road segment is planar and straight, the vanishing point in the road direction is extracted automati-cally by exploiting lane demarcations. Thus, the projective distortion of the road surface can be re-moved allowing affine rectification. Consequently, given one known ground distance along the road axis, 1D measurement of vehicle position in the correctly scaled road direction is possible. Vehicles are automatically detected and tracked along frames. First, the background image (the empty road) is created from several frames by an iterative per channel exclusion of outlying colour values based on thresholding. Next, the subtraction of the background image from the current frame is binarized, and morphological filters are employed for vehicle clustering. At the lowest part of vehicle clusters a window is defined for normalised cross-correlation among frames to allow vehicle tracking. The reference data for vehicle speed came from rigorous 2D projective transformation based on control points (which had been previously evaluated against GPS measurements). Compared to these, our automatic approach gave a very satisfactory estimated accuracy in vehicle speed of about ±3 km/h.	en
heal.fullTextAvailability	true
heal.conferenceName	FIG-ISPRS-ICA International Symposium on Modern Technologies, Education & Professional Practice in Geodesy & Related Fields.	en
heal.conferenceItemType	full paper