Abstract
The video object mechanism is based on the appearance representation of the object. Tracking objects in a video has applications in video surveillance and other some applications. In previous method does not handle the case of full occlusion. The case of full occlusion can be handled by setting an LSK similarity threshold, which stops tracking when the object is lost. The objects can be tracked based on the compression domain and pixel domain. The spatial information of the object that is being tracked is retrieved using Local Steering Kernels. The Color features are extracted using color histograms. The features similarities between a candidate object ROI and the object ROI in the previous frame and the last stored object instance in the object model are measured. For extracting the foreground extended Kalman filter is used. This increases the tracking efficiency of the algorithm. Index Terms: Color histograms, localsteeringkernels, and visualobjecttracking.
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