Adaptive Bootstrapping Management by Keypoint Clustering for Background Initialization
The availability of a background model that describes the scene is a prerequisite for many computer vision applications. In several situations, the model cannot be easily generated when the background contains some foreground objects (i.e., bootstrapping problem). In this letter, an Adaptive Bootstrapping Management (ABM) method, based on keypoint clustering, is proposed to model the background on video sequences acquired by mobile and static cameras.