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dc.contributor.authorPakpoom Prommoolen_US
dc.contributor.authorSansanee Auephanwiriyakulen_US
dc.contributor.authorNipon Theera-Umponen_US
dc.description.abstract© 2016 IEEE. Automatic tracking vehicle in urban traffic video surveillance is a challenging problem in computer vision. Although many issues have been solved, some are still unsolved, such as video surveillance problem of complex traffic intersection in congested condition. In this paper, we develop a vehicle counting system using a motion estimation with Taylor series approximation with embedded virtual entering and exiting boxes. The result shows that the system provides the counting success rate as high as 100% and the lowest counting rate is 14.29%. The mistakes are from the wrong direction prediction because of the very complex traffic condition.en_US
dc.subjectComputer Scienceen_US
dc.titleVision-based automatic vehicle counting system using motion estimation with Taylor series approximationen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleProceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016en_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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