Object tracking in real environments
Alexander M. Nelson, Jeremiah J. Neubert · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2010
Modern tracking methods typically rely on features to track objects. These methods function best with objects containing distinguishable features. Previously we proposed a graph cuts approach that utilizes intensity changes and the likelihood that the RGB intensities associated with a pixel belong to the object. We propose a new method that models the RGB tuple as a single random variable. This allows for more robust segmentation, but requires more data to construct the color model.The results show the ability of the method to tracking in a varity environments and with a large variety of objects.