An effective real-time mosaicing algorithm apt to detect motion through background subtraction using a PTZ camera

Nowadays, many visual surveillance systems exploit pan/tilt/zoom (PTZ) cameras to increase the field of view of a surveyed area. The background subtraction technique is widespread to detect moving objects with a high accuracy using one stationary camera. Extending such algorithms to work with moving cameras requires to have a background mosaic at one's disposal. Many solutions using mosaic background subtraction have been proposed, which offer real time capabilities or high quality of the detected objects. However, most of them rely on prior assumptions which limit the camera motion or the algorithm to work with a depth field of view only. In this work we propose some innovative solutions to achieve a real time mosaic background apt to work with existing background subtraction algorithms to yield excellent foreground object masks. Extensive experiments accomplished on challenging indoor and outdoor scenes permit to assess the quality of the mosaic as well as of the detected moving masks.