dc.contributor.authorWong, Cheng Hao
dc.date.accessioned2016-05-24T02:34:48Z
dc.date.available2016-05-24T02:34:48Z
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/10356/68008
dc.description.abstractWhile software computing has gained its popularities among numerous industrials and real-life applications, safe driving has always been a top priority in the automotive industry. Without a doubt advanced driving assistance systems are part of the enhancement that automobile manufacturers can improve on to keep their competitive edge in the market. While a typical driving assistance system includes detection of humans, road lanes to provide early warnings to driver, avoiding drifting out of road or even fatal collision. This project comprises the aspect of Piotr Dollár’s Matlab Toolbox and techniques of integral channel features applied in object detection to develop into vehicle detection. And base on two key factors, the feature representation and the learning algorithm, we would determine the performance of vehicle detection system. Additionally incorporating symmetric feature design along the vertical axis to further improve vehicle detection from the existing codes; measurement of efficiency is also illustrated in the closure of the report.en_US
dc.format.extent70 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineeringen_US
dc.titleBuilding a low cost advanced driver assistance system : vehicle detectionen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorWang Gangen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeELECTRICAL and ELECTRONIC ENGINEERINGen_US


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