Optimal window size for visual tracking for uniform CCDs

In this paper it is shown that for any form of visual tracking (the tracking of an object with visual feedback) tracking performance can be optimised by optimising the size of the tracking image window. The optimality criterion is the maximal change in predicted feature position, which is proportional to instantaneous acceleration, the biggest problem in tracking. The result is that optimal window size is reached when the time to process the image data equals the time of sampling the image. This result is valid for all algorithms whose calculation time is proportional to the area of the window. Linear windows can improve performance if the feature can be found within a linear window