搜索资源列表
Adaptive_background_mixture_models
- 混合高斯模型的经典文章，费了我好大的劲才能找到-Gaussian mixture model of the classic article, took me to find a good big Jin
cvbgfg_gaussmix
- 利用混合高斯模型进行前景检测的源代码实现，依据的是Stauffer发表的Adapptive background mixture models for real-time tracking.-The prospects for the use of Gaussian mixture model, detection of the source code implementation, based on the Stauffer published Adapptive background mix
basedoncolorsegment
- 为了提高非结构化道路识别算法的有效性,提出了一种道路分割的新方法,建立了道路区域和非道路区域混合高斯彩色模型,根据像素隶属于彩色模型的概率进行基于彩色信息道路 -In order to improve the effectiveness of unstructured road recognition algorithm presents a new method of road segmentation and establish the way of regional and off-roa
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- 基于混合高斯背景建模和阴影抑制算法, 可以消除混合背景下的阴影-mixture gaussian model(GMM)
detect
- 基于混合高斯建模的运动检测论文包。内含PDF 和NH格式-Gaussian mixture modeling based on motion detection paper bag.
sMOG_ChangeUpdateRate_DilationErosion
- simulink下封装的混合高斯的s-funcion函数。用于模型模块的搭建。-simulink package under the Gaussian mixture of s-funcion function. The structures used to model the module.
motiondetect
- 实现基于混合高斯模型的运动目标检测算法的仿真-Achieved based on Gaussian mixture model simulation of moving target detection algorithm
mixture_of_gaussians
- 基于混合高斯背景建模的理论思想，实现运动目标检测，检测效果理想-Gaussian Mixture Background Modeling Based on the theory of ideology, to achieve moving target detection, test results are satisfactory
MixtGaussian
- 这是基于em算法混合高斯模型参数的估计方法，用matlab开发的，看一遍程序就会明白了。-mixture Gauss estimation
LiuMixGauss
- 混合高斯模型背景建模，适用于视频跟踪，目标分割。 -GMM background modeling for video tracking, object segmentation.
matlabGMM
- 用matlab编的混合高斯模型的背景建模方法，可以参考一下。-Matlab compiled using a mixed Gaussian model of background modeling method, you can reference.
gmm2n
- 集合混合高斯模型的图像目标分割算法的VC实现-Gaussian mixture model for image set goals to achieve segmentation algorithm VC
mtest_new5_simple1
- matlab实现的对样本视频的混合高斯模型的检测代码-Sample video detection code Gaussian mixture model
mixture_of_gaussians
- 基于混合高斯模型的背景减除算法实现。matlab代码。-Gaussian mixture model-based background subtraction algorithm. matlab code.
backgroundmix
- 混合高斯建模，基于OPENCV，调试通过，对初学都有很大帮助-Gaussian mixture modeling, based on OPENCV, debugging through, is very helpful for beginners
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.
SiftGPU-V360
- SiftGPU 是SIFT特征为GPU执行。 SiftGPU进程像素平行建立高斯金字塔的技术要点。基于GPU的清单生成，SiftGPU然后使用的GPU / CPU的混合方法，有效地建立紧密特征点的名单。并行处理技术要点最后得到他们的方向和描述。-SiftGPU is an implementation of SIFT for GPU. SiftGPU processes pixels parallely to build Gaussian pyramids and detect DoG Key