基于Davinci-DM6467的高斯混合模型算法的实现

针对智能监控中运动目标检测的问题,提出了基于Davinci-DM6467的高斯混合模型像素级的背景分割策略。对彩色图像建立高斯混合模型,根据场景中象素点的稳定性来调整模型参数的更新速率;通过和马氏阈值进行对比来判断是不是要更新背景模型;通过和背景阈值进行对比来判断哪几个模型是属于背景区域。经验证性实验测试,结果表明,高斯混合模型在运动检测中实时性好,对环境有较强的鲁棒性。

Realization of gaussian mixture model algorithm based on Davinci-DM6467

In the light of movement target detection during intelligence monitoring,the author put forward Gaussian mixture model of pixel level background segmentation strategy based on Davinci-DM6467.Firstly establishing Gaussian mixture model for colorful images and then adjusting the updating velocity of model parameters according to the stability of each pixels in frames;secondly comparing them with Markov threshold to judge whether to update the background model;finally comparing them with background threshold to judge which several models belong to background region.Experimental results show that Gaussian mixture model in motion detection is possessed of good real-time and strong robustness to environment.