Motion tracking with non-stationary camera based on area and level set weighted average of centroid shifting vectors

In this paper, we propose a new representation of the location of the target that aims for the application of object tracking with non-stationary cameras and non-rigid motion: the area weighted mean of the centroids corresponding to each color bin of the target. With this representation, the target localization in the next frame can be achieved by a direct one step computation. The tracking based on this representation has several advantages such as being possible to track in low-rate-frame environment, allowing partial occlusion and being fast due to the one step computation. We also propose a background feature elimination algorithm which is based on the level set based bimodal segmentation and is incorporated into the tracking scheme to increase the robustness of the scheme.