Viewpoint independent vehicle speed estimation from uncalibrated traffic surveillance cameras

We present here a prototype of an algorithm for vehicle speed estimation. Different from previous approaches, our algorithm requires no road markers and fewer manual calibrations. Based on specific projection rules, we find a relation between the in-camera coordinate and the real world coordinate. A...

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Bibliographic Details
Main Authors: Haili Mao, Chengxi Ye, Mingli Song, Jiajun Bu, Na Li
Format: Conference Proceeding
Language:English
Subjects:
Calibration
camera calibration
Cameras
Kalman filter
Land vehicles
Parameter estimation
projection model
Radar tracking
Road vehicles
Surveillance
surveillance camera
tracking
Traffic control
Vehicle detection
Vehicle speed estimate
Video sequences
Online Access:Request full text
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Description
Summary:We present here a prototype of an algorithm for vehicle speed estimation. Different from previous approaches, our algorithm requires no road markers and fewer manual calibrations. Based on specific projection rules, we find a relation between the in-camera coordinate and the real world coordinate. A non-linear regression is employed to estimate the model parameters. This model enables us to estimate the real world position of the vehicles directly from a video sequence taken by a surveillance camera. The algorithm shows its ability to produce accurate estimations in our experiments.
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.2009.5346288