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
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.
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
Gussian
- 基于混合高斯模型的背景减除法，用于分离前景和背景-Background subtraction method based on Gaussian mixture model for separating the foreground and background
Moving-Object-Detection
- 混合高斯模型，目标检测，目标分割，区域标记-Gaussian mixture model, target detection, target segmentation, region
Foreground-detection-procedures
- 前景检测程序，MATLAB实现，有背景差分，帧差法，混合高斯模型，光流法。-Foreground detection procedures, MATLAB, background difference, frame difference method, the gaussian mixture model and optical flow method.
Improved-hybrid-Gauss
- 本文主要是针对传统混合高斯模型运动目标检测算法的不足做出了一些改进-This article is for the shortcomings of traditional Gaussian mixture model moving object detection algorithm made some improvements