Efficient Incorporation of Motionless Foreground Objects for Adaptive Background Segmentation

摘要

In this paper, we want to exploit the knowledge obtained from those detected objects which are incorporated into the background model since they cease their movement. These motionless foreground objects should be handled in security domains such as video surveillance. This paper uses an adaptive background modelling algorithm for moving-object detection. Those detected objects which present no motion are identified and added into the background model, so that they will be part of the new background. Such motionless agents are included for further appearance analysis and agent categorization.