What is it about?
Automatic estimation of traffic density via computer vision
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Why is it important?
Reliably estimating traffic density and providing an early warning to drivers on road conditions is important for mitigating the negative effect of slow traffic flow. In this work, video imaging tracking efficiency of vehicles is improved, as it has the advantage of providing spatial traffic information that are not related to a single point as in intrusive detectors.
Perspectives
A new video scene analysis method was introduced for road traffic congestion estimation. The method combines both morphological operations for vehicle detection and speed estimation, and Local Binary Pattern entropy for video scene randomness measurement. The road traffic congestion is classified onto a 5-level scale that represents the various possible conditions of road flows. Results show the usefulness of this method when applied to different road flows at peak and off-peak times.
Dr Omar S Al-Kadi
University of Jordan
Read the Original
This page is a summary of: Road scene analysis for determination of road traffic density, Frontiers of Computer Science, May 2014, Springer Science + Business Media,
DOI: 10.1007/s11704-014-3156-0.
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