Abandoned object detection using operator-space pursuit

This work presents a framework to be used in the detection of abandoned objects and other video events in a cluttered environment with a moving camera. In the proposed method a target video, that may have features we would like to detect, is compared with a pre-acquired reference video, which is assumed to have no objects nor video events of interest. The comparison is carried out by way of the achieved optimized operators, generated from the reference video, that produce Gaussian outputs when applied to it. Any anomaly of interest in the target video leads to a non-Gaussian output. The method dispenses with the target and reference videos being either synchronized or precisely registered, being robust to rotations and translations between the frames. Experiments show its good performance in the proposed environment.