关键词: 背景建模, 记忆模型, 聚类, 运动目标

Abstract: In some gradient and repetitive motion modeling scenes, traditional Gaussian mixture background modeling has a good effect. But the algorithm needs a large amount of computation and storage space, and it can neither fit for complex background or background with sudden changes. To solve these problems, a new clustering background modeling based on human memory model is proposed. Combined with human memory model, the algorithm sets up a cluster model for each pixel, and each cluster can be adaptively created, updated and deleted according to background changes. The algorithm makes accurate judgments according to human ultra-short-term memory, short-term memory and long-term memory, and the moving target detection results can meet the judgment of the human sensory organs.

Key words: background modeling, memory model, cluster, moving target