Adaptive Background Generation for Video Object Segmentation

In this paper, we present a novel method for generating background that adopts frame difference and a median filter to sensitive areas where illumination changes occur. The proposed method also uses fewer frames than the existing methods. Background generation is widely used as a preprocessing for video-based tracking, surveillance, and object detection. The proposed background generation method utilizes differences and motion changes between two consecutive frames to cope with the changes of illumination in an image sequence. It also utilizes a median filter to adaptively generate a robust background. The proposed method enables more efficient background reconstruction with fewer frames than existing methods use.