搜索资源列表
xiaobo
- ．首先，建 立背景的混合高斯分布模型和阴影颜色模型，通过差分法提取前景区域并结合Gabor小 波纹理特征分析找出潜在的阴影点；然后通过阴影颜色模型对这些潜在的阴影点进行颜 色分析；最后通过后续处理，找出真正的阴影区域-. First of all, to establish the background Gaussian mixture distribution model and the shadow color model, by differential extraction
mixGMMmatlab
- 混合高斯建模方法是目标检测中的一种重要方法- mix gauss detection object
grayplay
- 使用3阶混合高斯模型进行运动目标提取并进行背景更新-Using Gaussian mixture model of order 3 moving object extraction and background update
GMM_bg_ex
- Visual C++ 与 Opencv 联合实现的混合高斯模型背景提取与更新。-Opencv Visual C++ and the joint implementation of the Gaussian mixture model background extraction and updating.
GMM
- 混合高斯模型做的视频跟踪系统，具有良好的跟踪效果-Gaussian mixture model to do a video tracking system, has a good tracking results
GMM
- 建立了混合高斯模型，可以对静止背景下运动目标进行检测。-Gaussian mixture model is established, you can still detect moving target in the background.
emcenter
- 我写的改进中心点的混合高斯分布的EM算法-I wrote to improve the center of the EM algorithm for Gaussian mixture
demo1
- 我自己写的关于二维混合高斯分布的EM算法-I wrote about the distribution of two-dimensional Gaussian mixture EM algorithm
yundongjiance
- 运动视频的背景建模与运动物体的检测，包含混合高斯模型和帧差法检测运动物体。使用opencv编写-failed to translate
mixture_of_gaussians
- 这个代码适用于检测运动目标，基于混合高斯建模的运动目标检测。-this code can help you detection some objects，such as car，people，and so on. which based on mixture of gaussians background model
js_gmm_Lee
- 根据Lee与2005年发表的混合高斯模型背景建模的论文编写的源代码，可以作为对GMM算法改进的一个参考。-According to Lee s paper published in 2005 about GMM background modeling, it is written in C. It should be a reference for those who are intrested in GMM algorithm improvement.
GMM3
- 基于混合高斯模型的运动目标检测，能实时检测出完整运动前景，是本人对原来的高斯模型的改进-Gaussian mixture model based motion detection, real-time full motion detection prospects are my original Gaussian model improvements
mulgmm
- 利用混合高斯模型对图像序列经行背景建模，并保存。（附图片）-Using Gaussian mixture model for background modeling image sequences through the line and save. (With pictures)
mixture_of_gaussians
- 这个程序是基于混合高斯背景模型的运动目标检测算法，m文件和所用视频放到matlab的工作目录下即可运行-This program is based on the Gaussian mixture background model of moving target detection algorithm, m, and used video files into matlab working directory to run
mixture_of_gaussians
- 混合高斯模型使用K（基本为3到5个） 个高斯模型来表征图像中各个像素点的特征,在新一帧图像获得后更新混合高斯模型,用当前图像中的每个像素点与混合高斯模型匹配,如果成功则判定该点为背景点, 否则为前景点。-training video with GMM model ,then get the background,and store the picture in your computer.
GMM
- 一种改进的混合高斯模型（GMM）算法，加入形态学滤波与团块处理算法，运动目标提取效果良好。(An improved hybrid Gauss model (GMM) algorithm, which combines morphological filtering and blob processing algorithm, achieves good moving target extraction.)
GMM
- 用java实现混合高斯模型，做特征分类，模式识别等应用(The hybrid Gauss model is implemented by Java, and the feature classification and pattern recognition are performed)
EM_GMM
- 用EM算法对混合高斯模型中的参数进行估计 一种改进的EM算法即Monte Carlo EM算法（MCEM）的一个简单例子(The parameters in the mixed Gaussian model are estimated by EM algorithm An improved EM algorithm is a simple example of the Monte Carlo EM algorithm (MCEM))
相邻帧差法提取运动目标并计时
- 混合高斯模型提取运动区域算法。。。。。。。。。(Hybrid Gauss model for moving region extraction)
背景差GMM
- opencv，vs2010 利用混合高斯模型，得到运动前景，与静态背景(Opencv and VS2010 use hybrid Gauss model to obtain motion foreground and static background)