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运动目标检测是计算机视觉、模式识别、视频编码、基于内容的检索等领域的研究重点和难点，在视频监控、虚拟现实、机器人导航等许多领域得到广泛应用。针对运动目标检测中的动态背景问题，提出一种多分辨率互补检测方法。首先，通过对图像进行降低分辨率和高斯模糊来减少动态纹理和背景扰动的影响，在低分辨率下对图像进行区域分割，基于直方图特征使用IIR滤波器法建立低分辨背景模型，并检测出可能存在运动目标的区域；然后，对于高分辨率图像，基于自适应的混合高斯模型，对低分辨率下检测到的可能存在运动目标的对应区域进行目标检测，修正低分辨率的背景模型，实现多分辨率互补检测过程。“,”Nowadays motion detection under dynamic background has been an important and difficult research area of computer vision and video processing. For motion detection in the dynamic context, a complementary multi-resolution detection method is proposed. Dynamic textures and background disturbances in images are reduced by lowering the image resolution and applying Gaussian blur. First, the low-resolution image is segmented into blocks, and then the background model is built using histogram characteristics obtained by IIR filters to detect the possible areas that moving target probably exists;then, the motion detection is executed on the high-resolution image based on adaptive Gaussian model in the corresponding detected regions in the low resolution image, and the learning rates of low-resolution model are refined with the detection results, so the complementary multi-resolution detection process is implemented.