Traditional background subtraction algorithms assume the camera is static and are based
on simple per-pixel models of scene appearance. This leads to false detections when the
camera moves. While this can sometimes be addressed by online image registration, this
approach is prone to dramatic failures and long-term drift. We present a novel background
subtraction algorithm designed for pan-tilt-zoom cameras that overcomes this challenge
without the need for explicit image registration. The proposed algorithm automatically trains …