Please use this identifier to cite or link to this item: https://repository.cihe.edu.hk/jspui/handle/cihe/2303
DC FieldValueLanguage
dc.contributor.authorSiu, Wan Chien_US
dc.contributor.otherWong, C.-C.-
dc.contributor.otherJennings, P.-
dc.contributor.otherBarnes, S.-
dc.contributor.otherFong, B.-
dc.date.accessioned2022-02-17T05:54:17Z-
dc.date.available2022-02-17T05:54:17Z-
dc.date.issued2015-
dc.identifier.urihttps://repository.cihe.edu.hk/jspui/handle/cihe/2303-
dc.description.abstractThis paper presents a novel algorithm for the detection and tracking of low relative speed moving vehicles. The proposed algorithm is particularly suitable for mass-produced in-vehicle devices as it combines with motion vector based moving object detection to form a complete solution for an Advanced Driver Assistance System given its reduction in cost and complexity. The algorithm utilizes motion vectors that are readily available from video encoder output. The region of interest for detection is reduced by ignoring the area above the vanishing line of the captured image, evaluation of the amplitude of motion vectors and identification of the road region. During the evaluation process, a binary image is generated by comparing the gray-level of the captured image to the gray-level of the detected road region. Subsequently, the horizontal and vertical contours of specific areas inside the region of interest are evaluated. Test results show the effectiveness of the algorithm with more than 90% detection rate and the suitability for real-time use with cycle time of less than 66ms.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofIEEE Transactions on Consumer Electronicsen_US
dc.titleA smart moving vehicle detection system using motion vectors and generic line featuresen_US
dc.typejournal articleen_US
dc.identifier.doi10.1109/TCE.2015.7298299-
dc.contributor.affiliationSchool of Computing and Information Sciencesen_US
dc.relation.issn1558-4127en_US
dc.description.volume61en_US
dc.description.issue3en_US
dc.description.startpage384en_US
dc.description.endpage392en_US
dc.cihe.affiliatedNo-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.grantfulltextnone-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.openairetypejournal article-
crisitem.author.deptSchool of Computing and Information Sciences-
crisitem.author.orcid0000-0001-8280-0367-
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