对于固定场景中的复杂背景图像序列的运动目标检测问题，采用单高斯模型和区域高斯模型的级联式检测方法，并在区域高斯模型的更新过程中引入了自组织映射的“竞争、合作”机制，提出一种基于自组织映射的区域高斯模型算法。该算法不仅能够在水波纹和树叶晃动等复杂背景环境中检测运动目标，并且能够保证检测运动目标的相似性。使用PETS2002和Water Surface复杂背景图像序列的仿真结果验证了算法的有效性。

A self-organization mapping based region Gaussian model algorithm is proposed, which can detect moving objects in complex background image sequences of the static scene. This algorithm combined single Gaussian model with region Gaussian model to form a cascading detection method, and the “competition & cooperation” mechanism was introduced in the step of region Gaussian model updating. This method can not only detect moving objects efficiently at the scene of shaking leaves, waving water surface and other complex background, but also guarantee the integrity of detected objects. Through the experiments of PETS2002 and Water Surface image sequences, the characteristic of proposed algorithm was validated in various environments with complex background.