搜索资源列表
隐马尔可夫模型源代码
- 隐马尔可夫模型源代码.rar -hidden Markov model source code. Rar hidden Markov model source code. Rar
隐马尔科夫模型 c代码
- 隐马尔科夫模型 c代码
activecontour.关于主动轮廓模型的c++程序
- 关于主动轮廓模型的c++程序，详细说明了snake轮廓模型内部外部能量函数的求取等。,On the active contour model of the c++ program, details the snake contour model of internal and external energy function to strike and so on.
sho.rar
- 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
code.rar
- 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
gmm_test.rar
- 使用EM算法模拟高斯混合模型（GMM）的构成,Analog EM algorithm using Gaussian mixture model (GMM) the composition of
cluster.rar
- 用高斯混合模型进行数据聚类分析的matlab 程序。,Set of files for analysis of Gaussian mixture models for data set clustering etc.
Background_GMM.rar
- 混合高斯模型，建立背景模型，从而可以分离前景与背景,Gaussian mixture model, background model, which can be separated from foreground and background
GuassionModel.rar
- 基于混合高斯模型的运动目标检测，值得学习，对背景更新相当有效,opencv程序
用高斯模型来进行相似度计算
- 这是一个用高斯模型来进行相似度计算 然后，采用模板匹配的算法实现人脸的检测和定位的。,This is a Gaussian model used for similarity computation and then, using a template matching algorithm of face detection and positioning.
GMM
- 本代码建立高斯混合模型(高斯多模型)(GMM)，将其用于计算机视觉领域的视频目标检测/视频监控/运动检测/运动目标检测/视频目标跟踪等相关应用中。-This code sets up Gaussian mixture model(Gaussion Mixture Model, GMM) with image sequences for the research and application field of computer vision, using GMM for visual objec
BGFG_CODEBOOK
- 基于码书的运动目标检测是和混合高斯模型（MoG，GMM）类似的而简单有效的背景剪除方法，附件是VC++6.0编写的基于码书的运动目标检测，可直接读取摄像头，也可改为读取硬盘视频文件，需安装Opencv1.1-Codebook-based moving target detection and Gaussian mixture model (MoG, GMM) and a similar cut off the background simple and effective method of a
GVF_BY_XU
- XU等人做的关于GVF的小DEMO，里面比较了和传统蛇模型的不同之处以及GVF的优点，可以借此做些改进-XU and other people to do about the GVF small DEMO, which compared the traditional snake model and the differences as well as the advantages of GVF can be done to improve
LCV 局部区域活动轮廓模型
- 这是“An efficientlocalChan–Vesemodelforimagesegmentation”（简称LCV模型）的MATLAB源代码。LCV模型是非常重要局部区域活动轮廓模型，它被广泛使用于各个领域，如MRI大脑图像分割，血管图像分割，图像偏差场纠正。-This is "An efficientlocalChan-Vesemodelforimagesegmentation" (referred to as the LCV model) of the MATLA
DIP
- 图像的操作，及视频流的相关操作，基于opencv，运动目标检测，中值滤波，高斯背景模型，混合高斯模型-The operation of the image, and video streams related operations, based on the opencv, motion detection, median filtering, Gaussian background model, Gaussian mixture model
ASM
- 主动形状模型，实现轮廓提取有一定的帮助。-Active Shape Model
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.
GMM
- 实现混合高斯模型的聚类算法 利用最大似然估计和最大期望的方法来实现混合高斯模型-Gaussian mixture model to achieve clustering algorithm using the maximum likelihood estimation and the greatest way to achieve the desired mixed-Gaussian model
Implit_Function_And_Marching_Cube
- 实现了3D模型变形（morphing）的隐函数插值算法。并有Matching Cube算法网格化模型。这个程序花了我不少时间编写。-Achieved a 3D model of the deformation (morphing) of the implicit function interpolation algorithm. And Matching Cube Mesh count model. This process gave me a lot of time to prepare.
词袋模型最终版测试
- 利用词袋模型，实现对Merchdata数据库内图像的标注功能。使用了bagoffeatures库函数。(The bag-of-words model is used to implement the annotation of images in the Merchdata database. Use the bagoffeatures library function.)