Motion-based easy initialization of online foreground segmentation

Online foreground segmentation usually requires to be initialized in order to specify the segmentation model. In real environments, re-initialization is also often required because of unexpected events that can break the segmentation process (e.g. unintentional movements of the camera). Traditional approaches for the initialization can not deal with common cases conveniently, especially in the situations that the segmentation process is frequently broken (e.g. network meeting with laptop). In this paper we propose a method that enables online segmentation to be initialized easily. The core of our approach is a novel motion segmentation method, that is, the Segmentation from Small Motion (SfSM), which can accurately extract the foreground object based on its slight motion between two frames. To initialize the segmentation process, we first use SfSM to segment a series of frames, and then select the one with the highest confidence as the initialization frame. Unexpected events can be handled easily by detecting changes in the background, and then re-initialize the segmentation model in the changed scene. Experiments demonstrate that our method can effectively deal with common cases in a convenient way.