关键词: 运动目标检测, 帧间差分, 分块模型, 混合高斯模型

Abstract: This paper presents an improved algorithm of Gaussian mixture model based on inter-frame differencing blocking model and adaptive learning rate for the problem of too large calculation, poor ability to adapt to the complex scenes and other issues. It introduces the blocking model, effectively integrates information of pixel airspace, based on the inter-frame difference results, it determines the suspicious foreground region and background region to improve the detection sensitivity. Complex models are used for suspicious areas to ensure the accuracy of the moving-object detection and simple models are used to reduce the amount of computation. It passes through adaptive learning rate to accelerate the formation and regression of the background. Experimental results show the algorithm can take into account the detection accuracy and computational cost.

Key words: moving-object detection, inter-frame differencing, blocking model, Gaussian mixture model