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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/1555
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| Title: | Robust Real-Time Object Tracking Under Background Clutter |
| Authors: | Panda, D K
Meher, S |
| Keywords: | Video surveillance
Spatial resolution
intensity
object tracking
background clutter
fuzzy c-means |
| Issue Date: | Nov-2011 |
| Citation: | International Conference on Image Information Processing (ICIIP 2011) at JUIT Waknaghat, Simla, HP, 3-5 Nov 2011 |
| Abstract: | In this paper we propose a novel method for
detecting target object in presence of background clutter such as leaves of trees and changing illumination condition in real-time video and then tracking the object. A small movement in the
background such as leaves of trees and changing illumination condition affects the performance of the automated tracking system. Here in this paper, we reduce the spatial and intensity
resolution of an image to minimize the effects caused by the background clutter. A 3-frame-differencing method is employed to detect a moving object. Fuzzy c-means clustering is used to
segment the moving object from the background. The proposed method yields superior performance as compared to the other existing methods. |
| Description: | Copyright belongs to proceeding publisher |
| URI: | http://hdl.handle.net/2080/1555 |
| Appears in Collections: | Conference Papers
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Size | Format |
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| 1569481347_cr.pdf | | 1668Kb | Adobe PDF | View/Open |
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