Adaptive video background replacement

A video background replacement algorithm is proposed, which is based on background subtraction with adaptive background modeling. Like one early work ([1]) in this direction, it does not require a blue screen but needs only a pre-recorded background scene image. The problem is formulated as one that detects statistical outliers with respect to the given background. A two-pass process, which refines initial segmentation based on the statistics on a pixel’s neighborhood, is adopted in order to suppress false positives in the background region while increasing detection rate for the foreground object. Experiments with real image sequences are presented, along with comparisons with some other existing methods, illustrating the advantages of the proposed algorithm. 1