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dc.contributorMulti-disciplinary Studiesen_US
dc.contributorDepartment of Electronic and Information Engineeringen_US
dc.creatorWong, Ka-fai-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/3319-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleMotion-based head detection for lift control systemen_US
dcterms.abstractIn this project, a motion-based head detection system is developed to segment and count moving human heads from complex background. The constraint line clustering and the block based motion compensation approach with Higher Order Statistics (HOS) are implemented to produce velocity field clusters. The constraint line clustering approach provides a robust method for scalar motion field generation. The block based motion compensation approach with HOS generates motion field vectors of an image sequence, which aims to produce compact segments of objects for further recognition. Higher order statistics algorithm instead of a typical mean square error minimization algorithm is implemented to eliminate Gaussian noise. The performance of the detector is evaluated on a number of image frames with different illumination conditions and injection of noise. In addition, a color feature-based approach is developed to extract heads from segmented objects. The possible applications in industry are also discussed in this dissertation.en_US
dcterms.extentii, 100 leaves : ill. ; 30 cmen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2000en_US
dcterms.educationalLevelAll Masteren_US
dcterms.educationalLevelM.Sc.en_US
dcterms.LCSHImage processingen_US
dcterms.LCSHOptical pattern recognitionen_US
dcterms.LCSHPattern recognition systemsen_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsrestricted accessen_US

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