Video object tracking using region split and merge and a Kalman filter tracking algorithm

This paper proposes a reliable method for tracking the trajectory of video objects using the vector Kalman predictor. Video objects, within the scope of this paper, are defined as groups of image pixels coherent spatially as well as in their values of luminance. The extent to which the quality of the unsupervised region split and merge segmentation affects the accuracy of the tracker is discussed, alongside the improvements made in the segmentation process as a result of the feedback from the tracking algorithm. The overall low complexity of the system, and the time savings made in using a spiral search algorithm, provide this method with prospects of being implemented in real-time.