Traditional Gaussian Mixture Model (GMM) can’t adapt quickly to the sudden changes in the dynamic scene. A Metacognitive Model-based Intelligent Gaussian Mixture background modeling method is proposed. For each pixel, decision making must pass the three elements which are called as Metacognitive Monitoring (MM) element, Metacognitive Cognitive Knowledge (MCK) element and Metacognitive Experience (ME) element. MM element monitors the modeling scheme, stimulates to get ME element, and extracts cognitive knowledge from MCK element. MCK element is composed of the background models cognized ever. ME element is composed of the experiences from success or failure matching. In the complex scene, the proposed method can intelligently cognize background, quickly adapt to the sudden changes of backgrounds cognized ever and describe real background more accurately.