搜索资源列表
Gaussian-mixture-model
- 混合高斯模型GMM EM算法，建模效果好，可以用于行为识别-Gaussian mixture model GMM EM algorithm, modeling effect, can be used for behavior recognition
street1
- 对红外热感相机采集的图像进行处理，采用混合高斯模型进行前景提取，实现对画面里人的跟踪-Infrared thermal camera captured images are processed using Gaussian mixture model foreground extraction, to achieve the picture tracking
GMM
- 针对摄像机固定下的复杂背景环境，对采集到的视频图像的图像数据用混合高斯背景建模方法实现前景/背景分割，实现运动目标检测和跟踪。在进行前景检测前，先对背景进行训练，对图像中每个背景采用一个混合高斯模型进行模拟，每个背景的混合高斯的个数可以自适应。然后在测试阶段，对新来的像素进行GMM匹配，如果该像素值能够匹配其中一个高斯，则认为是背景，否则认为是前景。由于整个过程GMM模型在不断更新学习中，所以对动态背景有一定的鲁棒性。最后通过对一个有树枝摇摆的动态背景进行前景检测，取得了较好的效果。-For c
GMM
- 使用混合高斯模型对肝脏CT图片分四类，并显示分类结果。-Using Gaussian mixture model for liver CT images divided into four categories, and displays the classification results.
Gaussian
- 在VS2010中，利用openCV2.4.3写的基于混合高斯模型的运动目标检测。-moving object detection based on Gaussian mixture model in VS2010 and openCV2.4.3 ..
guassianmodel
- 对采集的视频图像序列进行基于混合高斯模型的背景建模，随着背景的不断更新，提取出的背景效果越来越好，但该方法不适合背景变化剧烈的场景。-Video capture image sequences based on background modeling Gaussian mixture model, with the background of constantly updated, the extracted background effect is getting better, but th
mixture_of_gaussians
- 混合高斯模型提取视频帧前景背景图像，经试验验证准确率比较高-Mixed gaussian model to extract video frame prospects background image
mixGaussEm
- matlab m文件 EM算法混合高斯模型-matlab m file EM algorithm Gaussian mixture model
BLS-GSM
- BLS-GSM代表“Bayesian Least Squares - Gaussian Scale Mixture(贝叶斯最小二乘-高斯尺度混合模型)”。 这个工具箱实现了该篇论文中介绍的算法： J Portilla, V Strela, M Wainwright, E P Simoncelli, Image Denoising using Scale Mixtures of Gaussians in the Wavelet Domain, IEEE Transaction
Video-detect
- 目标自动识别与跟踪系统，基于MFC界面和opencv视觉库，采用混合高斯进行目标识别，基于局部颜色直方图模型进行自动跟踪，并实现跟踪框可变，跟踪结果实时显示。-target detection and track system
BSG_GMM
- 背景检测算法，利用混合高斯模型，可以每一帧更新背景帧得到较好的结果-Background detection algorithm, using Gaussian mixture model, you can update each frame background frame to get better results
Hybrid-Gaussian
- 混合高斯模型，能够区分前景和背景。导入视频可世界运行。但是还没有去噪，可能对前景分析不够准确。-The code of Hybrid Gaussian,It can distinguish the difference of foreground and background.
hybrid-gaussian
- 混合高斯模型，提取前景和背景。效果勉强，可直接使用。-Mixed Gauss model, extraction of foreground and background.
run
- 基于混合高斯模型的背景减除实现程序，速度还可以，但是效果不是特别好，还有待改进-Gauss mixture model background subtraction procedure based on the implementation, can also speed, but the effect is not particularly good, there is room for improvement
GMM-GMR-v2.0
- 利用混合高斯模型对背景图像进行建模，所谓“混合高斯”的意思就是每个像素都是由多个单高斯分布混合组成的。-Name of the file which the classifier is loaded. Only the old haar classifier (trained by the haar training application) and NVIDIA s nvbin are supported for HAAR and only new type of OpenCV XML ca
bgfg_egmml
- 采用混合高斯模型对背景进行建模，然后对视频的运动目标进行检测！-By using the gaussian mixture model for background modeling, and then to detect the moving targets of video!
gmm
- EM算法以及混合高斯模型，c++实现，控制台程序，函数调用很简单方便。可以在低版本vc6.0运行。-EM algorithm and hybrid Gauss model, c++ implementation, the console program, function call is very simple and convenient. Can be run at low vc6.0.
npbayes
- 剑桥大学无参数贝叶斯课程的代码,主要包括狄利克雷过程，主题模型，无限混合高斯分布等-code of nonparametric bayesian cambridge， include dirichlet process, topic model, infinite mixutre gaussian
meanshift-tracking
- 本算法实现的是目标的跟踪，采用的是混合高斯模型建立背景，然后用meanshift进行跟踪，包括使用MFC进行界面编辑-The algorithm is to track the target, using Gaussian mixture model background, and then meanshift track, including the use of interfacial MFC edit
VBEMGMM
- 变分贝叶斯高斯过程混合模型源码，主要基于pattern recognition and machine learning 这本书。-22 Oct 2008 gmmVBEM.m is the main file for VBEM Main file needs MyEllipse.m for plotting Netlab gmmem for initialization Following example file illustrates the usa