Robust mean-shift tracking with extended fast colour thresholding

We propose a novel adaptive approach for object tracking using fast colour thresholding and region merging. It proves to be an effective measure against large variations between consecutive frames during a mean-shift process. The approach retains mean-shift´s property of efficiency and improves mean-shift´s drawback of robustness. It can track non-rigid objects with significant occlusion.