基于三帧差分混合高斯背景模型运动目标检测

针对混合高斯背景模型运动目标检测的光照突变误检以及突然运动目标的“鬼影”问题，提出了一种基于三帧差分的混合高斯背景模型运动目标检测算法。通过图像前景检测比例判断光照是否发生突变，利用三帧差分法对图像的背景区域、运动区域和背景显露区域进行划分，并根据光照情况及时改变各区域的学习率以调节混合高斯模型背景迅速更新，设计了基于三帧差分的学习率自适应混合高斯模型背景更新的方法。该方法使光照突变及目标突然运动后产生的新的背景模型得到迅速更新，从而改善这两种情况下运动目标检测效果。实验结果表明，该算法避免了光照突变时的大面积误检现象，并且同时解决了突然运动目标的“鬼影”问题。

Moving Object Detection Using Mixed Gauss Background Model Based on Three Frame Differencing

Aiming at the problem of moving object detection based on mixture of Gauss background model，mainly the false detection of light mutation and the“ghosting”of sudden moving object，an algorithm of moving object detection of mixed Gauss background model based on three frame differencing is designed． According to the proportion of the foreground of the image to judge whether the light is changed，the three frame difference method is used to divide the background area，the moving area and the exposed background area． According to the illumination，the learning rate of each region can be changed in time to adjust the update speed of the background of the mixed Gauss model，and a new method based on three frame difference and adaptive learning rate is proposed to update the background of mixed Gauss model． This method makes the new background model produced by abrupt illumination and sudden motion of the target rapidly updated，improving the detection result of moving objects in these two cases． The experimental results show that the moving object detection algorithm can avoid large area error phenomenon of illumination mutation，and solve the “ghost”problem of moving object．