文件名称:gaosi

  • 所属分类:
  • 2D图形编程
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2014-09-21
  • 文件大小:
  • 85kb
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  • 0次
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  • 快*
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高斯混合模型,概率统计知识,用于图像处理-Gaussian mixture model, probability and statistics knowledge, used in image processing
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高斯混合模型程序\1gmm\eStep.m

................\....\estimateMU.m

................\....\estimatePX.m

................\....\estimateZIGMA2.m

................\....\gmm.m

................\....\pyx.m

................\gmm_prob\gmm_prob\gmmactiv.m

................\........\........\gmmpost.m

................\参数估计EMalgorithmforMOG\sunMOG.m

................\.........................\testMOG4.m

................\视频检测GMM\GMM_高斯多模型_高斯混合模型\adaptive_video.m

................\...........\...........................\best_background_image.m

................\...........\...........................\display_result.m

................\...........\...........................\foreground_objects.m

................\...........\...........................\framedifference_video.m

................\...........\...........................\GMM_images.m

................\...........\...........................\GMM_video.m

................\...........\...........................\load_data.m

................\...........\...........................\mixture_parameters.m

................\...........\...........................\segment_image.m

................\...........\...........................\update_mixture_params.m

................\高斯混合模型GMM-EM\高斯混合模型的EM算法的源程序代码\参考源程序代码\cha.m

................\..................\................................\..............\data1.m

................\..................\................................\..............\data2.m

................\..................\................................\..............\Gao.m

................\..................\................................\..............\junzhi.m

................\..................\................................\..............\main.m

................\..................\................................\..............\Out.asv

................\..................\................................\..............\Out.m

................\..................\................................\..............\xie_matrix.m

................\..................\................................\..............\Z.m

................\..................\................................\..............\Z_matrix.m

................\..................\................................\..............\运行的结果.txt

................\..................\................................\实验报告.doc

................\..................\................................\封面.doc

................\..................\................................\源程序代码\cha.m

................\..................\................................\..........\data1.m

................\..................\................................\..........\data2.m

................\..................\................................\..........\Gao.m

................\..................\................................\..........\junzhi.m

................\..................\................................\..........\main.m

................\..................\................................\..........\Out.m

................\..................\................................\..........\xie_matrix.m

................\..................\................................\..........\Z.m

................\..................\................................\..........\Z_matrix.m

................\..................\................................\..........\运行的结果.txt

................\..................\................................\参考源程序代码

................\..................\................................\源程序代码

................\gmm_prob\gmm_prob

................\视频检测GMM\GMM_高斯多模型_高斯混合模型

................\高斯混合模型GMM-EM\高斯混合模型的EM算法的源程序代码

................\1gmm

................\gmm_prob

................\参数估计EMalgorithmforMOG

................\视频检测GMM

................\高斯混合模型GMM-EM

高斯混合模型程序

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