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EN
This paper presents a method to estimate vehicle speed automatically, including cars and motorcycles under mixed traffic conditions from video sequences acquired with stationary cameras in Hanoi City of Vietnam. The motion of the vehicle is detected and tracked along the frames of the video sequences using YOLOv4 and SORT algorithms with a custom dataset. In the method, the distance traveled by the vehicle is the length of virtual point-detectors, and the travel time of the vehicle is calculated using the movement of the centroid over the entrance and exit of virtual point-detectors (i.e., region of interest), and then the speed is also estimated based on the traveled distance and the travel time. The results of two experimental studies showed that the proposed method had small values of MAPE (within 3%), proving that the proposed method is reliable and accurate for application in real-world mixed traffic environments like Hanoi, Vietnam.
PL
W artykule przedstawiono wyniki symulacji śledzenia ruchu metodą Track-Before- Detect pozwalającą na pozyskiwanie informacji o ruchu obiektów w obecności silnego szumu. W przeprowadzonych badaniach symulacyjnych użyto zmodyfikowanego algorytmu TBD wykorzystującego superrozdzielczość, który pozwala na uzyskanie subpikselowej dokładności śledzenia ruchu.
EN
In the paper some simulations' results of motion tracking using the Track-Before-Detect method, allowing the acquisition of motion information in the presence of strong noise, are presented. Simulation experiments have been performed using the modified TBD algorithm utilising the super-resolution technique, which allow obtaining a sub-pixel accuracy of motion tracking.
EN
Most of the vehicles, which can be observed by the cameras used in the Intelligent Transport Systems, are coated with reflective layers which, like car windows, are characterized by the effect of light polarisation. Utilising this effect by using a camera designed for the Intelligent Transportation System along with the linear polarizer it is possible to improve the extraction of the vehicles from the surrounding. The article presents the methods of using the polarised light for increasing the operating range of the video systems along with an illustration of the possibilities and limitations of this technique. Some experimental results obtained by the fusion of data recorded for the standard video sequences and the use of linear polarisers are also presented.
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