dc.contributor.authorSatzoda, R. K.
dc.contributor.authorSuchitra, S.
dc.contributor.authorSrikanthan, Thambipillai
dc.contributor.authorChia, J. Y.
dc.date.accessioned2013-08-01T04:06:46Z
dc.date.available2013-08-01T04:06:46Z
dc.date.copyright2011en_US
dc.date.issued2011
dc.identifier.urihttp://hdl.handle.net/10220/12766
dc.description.abstractReal-time traffic queue detection can directly aid in dynamic traffic light control at road junctions. In this paper, we propose an efficient technique to detect vehicle queue lengths at traffic junctions based on progressive block based image processing. We also propose a two-step approach for vehicle detection that relies on edges and dark features in the image. It is shown that this vehicle detection approach is robust to heavy and light shadows. Further, the threshold adapts itself dynamically to handle varying light conditions. Evaluation of the proposed method using over 45 real video sequences shows nearly 100% accuracy in vehicle detection and queue length estimation.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Computer science and engineering
dc.titleVision-based vehicle queue detection at traffic junctionsen_US
dc.typeConference Paper
dc.contributor.conferenceIEEE Conference on Industrial Electronics and Applications (7th : 2012 : Singapore)en_US
dc.contributor.schoolSchool of Computer Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1109/ICIEA.2012.6360703


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