基于混合高斯模型的运动目标检测

针对运动目标检测中的背景复杂度高、视频数据计算量大等问题, 且为避免计算不同复杂程度的视频背景, 并能够准确地获取所需要的运动目标, 提出了一种基于混合高斯模型的运动目标检测方法. 首先采用混合高斯模型获取运动目标特征; 然后利用中值滤波方法去除视频目标运动特征中的背景噪声; 最后依据形态学运算方法对通过统计直方图得到的运动显著图进行处理, 从而获取最终的运动目标. 对标准视频序列集的检测表明, 利用该算法获取的运动目标不仅能抑制背景噪声, 而且精准度和误差都优于普通的视频运动目标检测算法.

. Moving target detection based on Gaussian mixture model and salience

Aiming at tackling the problems of high background complexity and large amount of video data in moving target detection, and in order to avoid computing the background of different complexity, a moving target detection method based on Gaussian mixture model is proposed. First, a Gaussian mixture model is used to acquire the features of the moving target, and then median filtering is applied to remove the background noise in the motion feature of the video target. Finally, by taking advantage of the morphological operation method, the motion image obtained by the statistical histogram is processed to obtain the final moving target. Tested on the standard video sequence set, the moving target obtained using the proposed algorithm can not only suppress the background noise, but also be better than the ordinary video moving target detection algorithm both in the accuracy improvement and error attenuation