Motion detection with an unstable camera

Fast and accurate motion detection in the presence of camera jitter is known to be a difficult problem. Existing statistical methods often produce abundant false positives since jitter-induced motion is difficult to differentiate from scene-induced motion. Although frame alignment by means of camera motion compensation can help resolve such ambiguities, the additional steps of motion estimation and compensation increase the complexity of the overall algorithm. In this paper, we address camera jitter by applying background subtraction to scene dynamics instead of scene photometry. In our method, an object is assumed moving if its dynamical behavior is different from the average dynamics observed in a reference sequence. Our method is conceptually simple, fast, requires little memory, and is easy to train, even on videos containing moving objects. It has been tested and performs well on indoor and outdoor sequences with strong camera jitter.