Dual-rate background subtraction approach for estimating traffic queue parameters in urban scenes

Abstract

This study proposes traffic queue-parameter estimation based on background subtraction. An appropriate combination of two background models is used: 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.