Please use this identifier to cite or link to this item: http://dspace.dtu.ac.in:8080/jspui/handle/repository/14452
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dc.contributor.authorGUPTA, KHUSHBU-
dc.date.accessioned2016-02-22T10:13:48Z-
dc.date.available2016-02-22T10:13:48Z-
dc.date.issued2016-02-
dc.identifier.urihttp://dspace.dtu.ac.in:8080/jspui/handle/repository/14452-
dc.description.abstractThis paper addresses face Detection and multifarious tracking using improved CamShift and texture algorithm. Face is detected by calculating texture information. And Object’s motion is taken into account through location and trajectory. Camshift is used to follow trajectory of the object. The Continuously Adaptive Mean Shift Algorithm (CamShift) is an adaptation of the Mean Shift algorithm for object tracking. It is a well-established and fundamental algorithm for kernel-based visual object tracking. It adjusts Search window itself in size. It will adjust itself for the size of face as the person moves closer or further from camera. And local binary pattern (LBP) technique is used to extract the texture features. LBP is a non-parametric kernel which summarizes the local spatial structure of an image and it is invariant to monotonic gray-scale transformations and rotation.en_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesTD NO.1226;-
dc.subjectFACE TRACKINGen_US
dc.subjectCAMSHIFTen_US
dc.subjectMULTIFARIOUS FEATURESen_US
dc.subjectLBPen_US
dc.titleFACE DETECTION AND TRACKING USING IMPROVED CAMSHIFTen_US
dc.typeThesisen_US
Appears in Collections:M.E./M.Tech. Electronics & Communication Engineering

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