Robust Background estimator using IMM

Intelligent video surveillance applications are frequently used nowadays. For such applications, background estimation becomes an important building block. In indoor environments, the switching of light takes place often. The previous approaches do not adapt quite well to the light switch. They take a long time to react to this problem. We attempt to tackle this problem by modeling it as a multiple model estimation problem. The well known IMM (interacting multiple model) estimator which has been successful in tracking maneuvering targets is used to tackle the light switch problem. The results show that it can easily detect the light switch with less error.