A New Moving-Object Invariant Video Mosaicing based method for Remote Surveillance A New Moving-Object Invariant Video Mosaicing based method for Remote Surveillance

A moving-object invariant video mosaicing technique applicable to the detection and monitoring activity over a wide area using an active camera has been proposed. There has been a large literature on image mosaicing, however, many of these algorithms focus on the static scene mosaicing using homography among the frames. There has also been recent work on activity monitoring and detection. Such work generally assumes a non-moving camera. In contrast, we propose a model for activity monitoring and detection over a wide area, where a moving camera is used to sweep over the area of interest and control through network or internet. Our approach is based on the combination of a proposed video mosaicing technique that has been used for constructing panoramic background and static registration along with adaptive background subtraction method that has been used for moving object detection and tracking. Unlike the conventional approach, the proposed mosaicing method employs motion clustering and segmentation techniques for automatically filtering moving objects from the resulting panorama and does not require any robust estimator for dominant motion estimation. We demonstrated the efficiency of our method by presenting results obtained from real life video data.