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dc.contributor.authorPanda, D K-
dc.contributor.authorMeher, S-
dc.identifier.citationInternational Conference on Image Information Processing (ICIIP 2011) at JUIT Waknaghat, Simla, HP, 3-5 Nov 2011en
dc.descriptionCopyright belongs to proceeding publisheren
dc.description.abstractIn 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.en
dc.format.extent1708072 bytes-
dc.subjectVideo surveillanceen
dc.subjectSpatial resolutionen
dc.subjectobject trackingen
dc.subjectbackground clutteren
dc.subjectfuzzy c-meansen
dc.titleRobust Real-Time Object Tracking Under Background Clutteren
Appears in Collections:Conference Papers

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