Pregled bibliografske jedinice broj: 705181
Real time vehicle detection and tracking on multiple lanes
Real time vehicle detection and tracking on multiple lanes // Poster Papers Proceedings of 22nd International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision WSCG2014 / Skala, Vaclav (ur.).
Plzeň: Vaclav Skala – Union Agency, 2014. str. 67-71 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 705181 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Real time vehicle detection and tracking on
multiple lanes
Autori
Kovačić, Kristian ; Ivanjko, Edouard ; Gold, Hrvoje
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Poster Papers Proceedings of 22nd International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision WSCG2014
/ Skala, Vaclav - Plzeň : Vaclav Skala – Union Agency, 2014, 67-71
ISBN
978-80-86943-72-5
Skup
22nd International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision WSCG2014
Mjesto i datum
Plzeň, Češka Republika, 02.06.2014. - 05.06.2014
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Multiple object detection ; intelligent transportation system (ITS) ; vehicle detection ; vehicle tracking ; algorithm parallelization ; trajectory estimation
Sažetak
Development of computing power and cheap video cameras enabled today’s traffic management systems to include more cameras and computer vision applications for transportation system monitoring and control. Combined with image processing algorithms cameras are used as sensors to measure road traffic parameters like flow, origindestination matrices, classify vehicles, etc. In this paper development of a system capable to measure traffic flow and estimate vehicle trajectories on multiple lanes using only one static camera is described. Vehicles are detected as moving objects using foreground and background image segmentation. Adjacent pixels in the moving objects image are grouped together and a weight factor based on cluster area, cluster overlapping area and distance between multiple clusters is computed to enable multiple moving object tracking. To ensure real time capabilities, image processing algorithm computation distribution between CPU and GPU is applied. Described system is tested using real traffic video footage obtained from Croatian highways.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo, Tehnologija prometa i transport
POVEZANOST RADA
Ustanove:
Fakultet prometnih znanosti, Zagreb
