This study proposes traffic queue‐parameter estimation based on background subtraction, by means of an appropriate combination of two background models: a short‐term model, very sensitive to moving vehicles, and a long‐term model capable of retaining as foreground temporarily stopped vehicles at intersections or traffic lights. Experimental results in typical urban scenes demonstrate the suitability of the proposed approach. Its main advantage is the low computational cost, avoiding specific motion detection algorithms or post‐processing operations after foreground vehicle detection.
Dual‐rate background subtraction approach for estimating traffic queue parameters in urban scenes
IET Intelligent Transport Systems ; 7 , 1 ; 122-130
2013-03-01
9 pages
Article (Journal)
Electronic Resource
English
long‐term model , post‐processing operations , traffic lights , foreground vehicle detection , queueing theory , object detection , background models , traffic engineering computing , motion detection algorithms , parameter estimation , dual‐rate background subtraction , urban scenes , traffic queue parameter estimation , temporarily stopped vehicles , short‐term model
Dual-rate background subtraction approach for estimating traffic queue parameters in urban scenes
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