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DC Field | Value | Language |
---|---|---|
dc.contributor.author | GUPTA, KHUSHBU | - |
dc.date.accessioned | 2016-02-22T10:13:48Z | - |
dc.date.available | 2016-02-22T10:13:48Z | - |
dc.date.issued | 2016-02 | - |
dc.identifier.uri | http://dspace.dtu.ac.in:8080/jspui/handle/repository/14452 | - |
dc.description.abstract | This 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.iso | en_US | en_US |
dc.relation.ispartofseries | TD NO.1226; | - |
dc.subject | FACE TRACKING | en_US |
dc.subject | CAMSHIFT | en_US |
dc.subject | MULTIFARIOUS FEATURES | en_US |
dc.subject | LBP | en_US |
dc.title | FACE DETECTION AND TRACKING USING IMPROVED CAMSHIFT | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | M.E./M.Tech. Electronics & Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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front pages.pdf | 280.35 kB | Adobe PDF | View/Open | |
thesis own(1).pdf | 1.27 MB | Adobe PDF | View/Open |
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