搜索资源列表
KNearestclass
- 使用K近邻算法对一个2维德样本集进行分类，样本集的分布为混合高斯分布。-K nearest neighbor to use a 2 Verde sample set for classification, the distribution of sample set for mixed Gaussian distribution.
CImGauMM_
- 高斯混合模型，及背景减计算，Blob连通域，统计流量计数-Gaussian mixture model, and background by calculation, Blob-connected domain, the number of statistical flowmeter
GMM_and_shadow_suppression
- 基于混合高斯的背景建模与阴影抑制算法研究,背景建模，目标检测-Based on Gaussian mixture background modeling and shadow suppression algorithm, background modeling, target detection
sho
- 基于c++的，运用opencv开发包的高斯混合模型，用于视频中运动物体的检测-Based on c++ And use the development package opencv Gaussian mixture model for moving objects in video detection
CvBSLibGMM
- 改进的高斯混合模型用于运动目标的检测和分割,利用C++和matlab混合编程.-Improved Gaussian mixture model for moving object detection and segmentation, the use of C++ and matlab programming mixed.
code
- 视频运动物体检测，采用混合高斯分布建立背景模型及差分方法对背景模型进行更新-Sports video object detection, adopt a mixed Gaussian distribution model and set up the background difference method to update the background model
Em
- 通过em算法实现对数据的高斯混合模型的分类-Em algorithm through implementation of data Gaussian mixture model classification
LiuMixGauss
- 关于自适应背景提取，是基于高斯模型的，效果很好-On adaptive background extraction is based on the Gaussian model, the effect of good
GMM
- 利用K-高斯混合模型提取视频的前景信息。-The use of K-Gaussian mixture model for the future of video information extraction
GMMS
- OPENCV下基于高斯混合模型的图像分割，程序中还有 基于大津法的图像分割和金子塔分割。-OPENCV Based on Gaussian mixture model of image segmentation, the program also includes Otsu method based on image segmentation and the segmentation pyramid.
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
bodymotiondetection
- 学习opencv图像处理中人体目标跟踪的一些很有用的资料，主要是讲camshift,meanshift和高斯混合模型。-Learning opencv image-processing for target tracking in the human body a number of very useful information, mainly speaking camshift, meanshift and Gaussian mix
GMM_background_src
- 基于有限混合高斯模型的数据分类 1、使用基于有限高斯混合模型的EM算法对数据样本进行归类 2、使用C++或者Matlab语言编程环境实现该算法，并用给定的数据包对算法的正确性进行检验 -Gaussian mixture model based on limited data classification 1, using the finite Gaussian mixture model based on EM algo
em-three-preference
- 基于EM算法，可以估计在混合高斯分布下的三个参数-EM expection
mixGuass
- 利用混合高斯模型进行前景提取，能够达到较好的检测结果-mix Guass， objects extracting
Gaussin-mixed
- 可以产生混合高斯信号信号的函数。自己可以调节混合信号的峭度。-Can produce mixed-Gaussian signal function. You can adjust the mixed signal kurtosis.
mixture-Gauss-model-EM-matlab
- EM算法计算混合高斯模型，可以计算三个参数。-Gaussian mixture model EM algorithm, three parameters can be calculated.
motion-detection-techniques
- 研究了基于混合高斯模型的运动目标检测技术,在分析了混合高斯模型的基本原理的基础上,使用了一种改进的混合高斯模型更新算法.在Visual C++6.0中利用OpenCV完成了相关算法,成功地提取出了运动目标和实验场景的背景,验证了该改进的混合高斯模型更新算法的可行性-OpenCV-based motion detection techniques I have read some articles, I feel you can, sha
一问 + 二问 VIBE_Code
- 用混合高斯模型进行背景处理，并能过滤微小的扰动，适用于动态背景(Use the mixed Gaussian model for background processing and to filter tiny perturbations for dynamic background)
hs
- Matlib代码，实现了光流法，高斯混合等(Matlib code, to achieve the optical flow, Gaussian mixture and so on)